Systems and methods to generate repair orders using a taxonomy and an ontology

ABSTRACT

Methods and apparatus are provided that are related to generating repair orders, including vehicular repair orders. A computing device can receive repair-related information associated with a repair order. The repair-related information can include information about a first repair attribute of one or more repair attributes. The computing device can determine a first ontology related to the first repair attribute. The first ontology can be further related to a first template. The computing device can determine modified repair-related information by at least utilizing the first template to modify at least a first portion of the repair-related information that includes the information about the first repair attribute. The computing device can generate an output related to the repair order that includes the modified repair-related information.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 16/046,930, entitled “Systems and Methods toGenerate Repair Orders Using a Taxonomy and an Ontology”, filed on Jul.26, 2018 and published on Nov. 15, 2018 as United States PatentApplication Publication No. US 2018/0330339 A1. U.S. patent applicationSer. No. 16/046,930 is a continuation application of U.S. patentapplication Ser. No. 15/185,863, entitled “Systems and Methods toGenerate Repair Orders Using a Taxonomy and an Ontology”, filed on Jun.17, 2016, published on Dec. 21, 2017 as United States Patent ApplicationPublication No. US 2017/0364870 A1, and issued on Sep. 4, 2018 as U.S.Pat. No. 10,068,207. U.S. patent application Ser. No. 15/185,863 andU.S. patent application Ser. No. 16/046,930 are incorporated herein byreference.

BACKGROUND

Vehicles, such as automobiles, light-duty trucks, and heavy-duty trucks,play an important role in the lives of many people. To keep vehiclesoperational, some of those people rely on vehicle technicians todiagnose and repair their vehicle.

Vehicle technicians use a variety of tools in order to generate repairorders, diagnose vehicles, and/or repair vehicles. Those tools mayinclude computers configured for data entry, common hand tools, such aswrenches, hammers, pliers, screwdrivers and socket sets, or morevehicle-specific tools, such as cylinder hones, piston-ring compressors,and vehicle brake tools. The tools used by vehicle technicians may alsoinclude electronic tools such as a vehicle scan tool or a digitalvoltage-ohm meter (DVOM), for use diagnosing and/or repairing a vehicle.

SUMMARY

In one aspect, a method is provided. A computing device receivesrepair-related information associated with a repair order. Therepair-related information includes information about a first repairattribute of one or more repair attributes. The computing devicedetermines a first ontology related to the first repair attribute, wherethe first ontology is further related to a first template. The computingdevice determines modified repair-related information by at leastutilizing the first template to modify at least a first portion of therepair-related information including the information about the firstrepair attribute. The computing device generates an output related tothe repair order including the modified repair-related information.

In another aspect, a computing device is provided. The computing deviceincludes one or more processors; and a non-transitory computer-readablemedium. The non-transitory computer-readable medium is configured tostore at least computer-readable instructions that, when executed by theone or more processors, cause the computing device to perform functions.The functions include: receiving repair-related information associatedwith a repair order, where the repair-related information includesinformation about a first repair attribute of one or more repairattributes; determining a first ontology related to the first repairattribute, where the first ontology is further related to a firsttemplate; determining modified repair-related information by at leastutilizing the first template to modify at least a first portion of therepair-related information including the information about the firstrepair attribute; and generating an output related to the repair orderincluding the modified repair-related information.

In another aspect, a non-transitory computer-readable medium isprovided. The non-transitory computer-readable medium is configured tostore at least computer-readable instructions that, when executed by oneor more processors of a computing device, cause the computing device toperform functions. The functions include: receiving repair-relatedinformation associated with a repair order, where the repair-relatedinformation includes information about a first repair attribute of oneor more repair attributes; determining a first ontology related to thefirst repair attribute, where the first ontology is further related to afirst template; determining modified repair-related information by atleast utilizing the first template to modify at least a first portion ofthe repair-related information including the information about the firstrepair attribute; and generating an output related to the repair orderincluding the modified repair-related information.

In another aspect, a device is provided. The device includes: means forreceiving repair-related information associated with a repair order,where the repair-related information includes information about a firstrepair attribute of one or more repair attributes; means for determininga first ontology related to the first repair attribute, where the firstontology is further related to a first template; means for determiningmodified repair-related information by at least utilizing the firsttemplate to modify at least a first portion of the repair-relatedinformation including the information about the first repair attribute;and means for generating an output related to the repair order includingthe modified repair-related information.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram of an example computing device, in accordancewith an embodiment.

FIG. 1B is a block diagram showing relationships between ontologies andtaxonomies, in accordance with an embodiment.

FIG. 2A is a diagram of electronic authoring tool software, inaccordance with an embodiment.

FIG. 2B is another diagram of electronic authoring tool software, inaccordance with an embodiment.

FIG. 2C and FIG. 2D depict example ontologies, in accordance with anembodiment.

FIG. 3A, FIG. 3B, FIG. 3C, and FIG. 3D depict example views of a userinterface of a computing device used for entering data for a repairorder, in accordance with an embodiment.

FIG. 4A, FIG. 4B, FIG. 4C, and FIG. 4D depict example views of anotheruser interface of a computing device used for entering data for a repairorder, in accordance with an embodiment.

FIG. 5A depicts an example view of a user interface of a computingdevice used for displaying a repair order, in accordance with anembodiment.

FIG. 5B depicts a flowchart for electronic authoring tool softwarerelated to the user interface depicted by FIG. 5A, in accordance with anembodiment.

FIG. 5C depicts an example view of another user interface of a computingdevice used for displaying a repair order, in accordance with anembodiment.

FIG. 5D depicts a flowchart for electronic authoring tool softwarerelated to the user interface depicted by FIG. 5C, in accordance with anembodiment.

FIG. 6A and FIG. 6B depict another flowchart for electronic authoringtool software related to the user interfaces depicted by FIGS. 5A and5C, in accordance with an embodiment.

FIG. 7 is a block diagram of an example computing network, in accordancewith an embodiment.

FIG. 8A is a block diagram of an example computing device, in accordancewith an embodiment.

FIG. 8B depicts an example network of computing centers, in accordancewith an embodiment.

FIG. 9 is a flow chart of an example method, in accordance with anembodiment.

DETAILED DESCRIPTION

Introduction

Herein are disclosed methods and apparatus related to generation ofrepair orders, such as repair orders for vehicles, where the vehiclescan include automobiles, trucks, boats, airplanes, and other motorvehicles. Personnel who enter repair orders may not be proficiententering in data related to repair orders and/or may not have sufficienttime to enter repair orders that accurately represent customercomplaints, conditions, symptoms and requests, particularly if such datais provided orally. To address these concerns, the herein-describedtechniques can provide structured procedures to describe complaints,conditions, symptoms, and requests using software utilizing repair-orderrelated ontologies and taxonomies. Using the herein-describedtechniques, repair order entry and generation can be sped up, theworkload on a person entering repair orders decreased, and the accuracyof data on the repair order can be increased. By generating repair orderdata using common formats and terminology, data mining and relatedsystems operating on the repair order data can be improved. Such datamining systems can spend less time pre-preprocessing the repair orderdata (such as interpreting and converting repair order terminology) andcan generate more accurate results, since these systems are operating onmore consistent data.

The herein-described techniques can enable generation of repair orders.For example, a computing device can receive repair-related informationassociated with a vehicular repair order. This repair-relatedinformation can include information complaints, conditions, symptoms,and requests provided by a customer (or customers) related to a repair,such as a vehicular repair. In particular, the repair-relatedinformation can include one or more repair “attributes”, or terms and/orphrases related to a repair. Such repair attributes can include, but arenot limited to, attributes of the repair including attributes relatedto: one or more symptoms, one or more occurrences of symptoms orcomplaints, one or more locations and/or spaces, one or more systems ofa vehicle (or other object to be repaired), one or more speeds, one ormore descriptions, audio, imagery, and/or conditions. The repairattributes can include vehicular-repair attributes associated with avehicular repair order.

The computing device can determine one or more ontologies related to therepair attributes. As described herein, an ontology can specify and/ordescribe one or more relationships between attributes. In some cases,the ontology can include one or more templates that specify and/ordescribe relationships of attributes. A template can includepredetermined and/or variable attributes. A predetermined attribute canbe an attribute unchanged by use of the template, and can be expressedin a template as a fixed string and/or other constant value(s), such as“idles”, “idles fast”, “40 MPH” (miles per hour), etc. A variableattribute can represent an attribute whose value can change by use ofthe template, and can be expressed in a template as a “tag” orplaceholder for a fixed value of the attribute; e.g., a “<component>”tag for a component attribute in the template.

Generally, a taxonomy can be, include, and/or refer to one or moredatasets (e.g., one or more databases, objects, listings, registries)storing information specifying and/or describing one or more attributes,where attributes can include words, terms, phrases, images, sounds, etc.And, generally an ontology can be, include, and/or refer to one or moredatasets storing information about concepts related to a topic, such asvehicular repair, that can be specified in terms of one or moreattributes; that is, an ontology can relate concepts about the topicspecified based on attributes that can be found in one or moretaxonomies. As an analogy to the taxonomies and ontologies discussed inmore detail herein, an English language dictionary can serve, at leastin part, as a taxonomy for a portion of the English language whose words(attributes) are specified in the dictionary, while an English languagegrammar book can serve, at least in part, as an ontology relatingattributes related to a topic; e.g., parts of speech in the Englishlanguage. In some embodiments, a taxonomy can include attributes relatedto multiple aspects; e.g., one taxonomy can include description-relatedattributes, condition-related attributes, speed-related attributes,and/or other attributes.

The computing device can modify repair-related information using thetemplate and/or other features of the ontology. For example,repair-related information can be modified by adding, removing,reordering, and/or changing one or more attributes in the repair-relatedinformation. Further, the ontology can be used to organize entry of therepair-related information.

Continuing the above-mentioned example, supposed a misspelled term“engin” is entered to specify a vehicular-repair-related customercomplaint using a computing device, where the computing device canaccess an ontology that includes the above-mentioned template T and oneor more related taxonomies. Then, the computing device can use theontology and/or the related taxonomies to determine that the term“engin” is a misspelled word related to the attribute “engine”, and thenchange the misspelled term “engin” to become “engine”. Then, if thephrase “fast idle” is entered to further specify the customer complaint,the computing device can access an ontology, and perhaps one or morerelated taxonomies, to determine a preferred term “idles fast” andreorder and modify the entered phrase “fast idle” to be the preferredterm “idles fast”. Additionally, the computing device can apply theterms “engine” and “idles fast” to the ontology to determine theabove-mentioned template T to specify the customer complaint.

Further, a template and/or other aspects of the ontology and relatedtaxonomies can be used to control a user interface for enteringrepair-related information. In one aspect, the user interface can beconfigured to accept one or more selections associated with the one ormore vehicular-repair attributes. Continuing the example above, thecomputing device can use the template T to instruct the user interfaceto prompt for the description, condition, and/or speed attributesspecified in template T. If these attributes are entered out of thedescription/condition/speed order specified by template T; e.g., thespeed can be specified before the description, the computing device canuse the order specified by template T to reorganize the enteredrepair-related information to specify the customer complaint as orderedby template T. For example, if the entered repair-related informationinclude the following terms “at high speed”, “intermittent”, and“accellertin”, the computing device can use template T and any relatedontologies and taxonomies to modify the entered repair-relatedinformation to be “The engine intermittently idles fast whileaccelerating at high speed”.

In another example, a customer can try to describe a sound made by avehicle to be repaired. Then, the computing device can play an audiofile (or other representation of audio information) to the customer,where the audio information is associated with one or more attributes.For example, an audio file recording the sound of squeaky brakes can beassociated with attributes such as “squeak” and/or “squeaky brakes” andanother audio file recording the sound of grinding brakes can beassociated with attributes such as “grind” and/or “grinding brakes”.When the customer agrees that the audio file replays a sound of thevehicle associated with the customer's complaint, then the computingdevice can update the customer's complaint and/or other repair-relatedinformation with information related to the one or more attributesassociated with the audio file (e.g., the attribute “squeaky brakes”, anattribute-related sentence “Customer hears a squeak.”). Further, therepair-related information can be modified to include (related) audio,such as the audio file identified by the customer, and/or (related)imagery information, such as images of a brake system, an image of thevehicle under repair, and/or video of brake pads being installed.

After modifying the repair-related information, the computing device cangenerate an output related to a (vehicular) repair order including themodified repair-related information. In some cases, the repair order canbe specified by templates and/or the ontology. For example, one templatecan specify that a repair order include a description of the customercomplaint, a diagnosis of the customer complaint, and a listing of partsand labor used to address the complaint. Another template can specifythat a repair order include a description of the customer's complaint, adiagnosis of the customer complaint, a listing of parts and labor usedto address the complaint, a graph of commonly repaired parts, and anindication of additional related parts, perhaps with a photo of therepaired vehicle. Many other repair orders and/or repair order templatesare possible as well.

Electronic Authoring Tool Software with Related Ontologies andTaxonomies

FIG. 1A is a block diagram of computing device 100, in accordance withan embodiment. Computing device 100 includes electronic authoring toolsoftware (EAT) 110, which can provide one or more user interfacesrelated to vehicular repair, such as graphical user interfaces and/orother user interfaces discussed below. For example, electronic authoringtool software 110 can be used to receive, modify, and outputrepair-related information; e.g., repair-related information related tovehicular repairs and repair orders. The repair-related information caninclude inputs such as entered complaint information regarding acustomer complaint that lead to a vehicular repair, cause informationabout one or more reasons for the customer complaint and perhaps otherreasons for repairs, vehicular information about a vehicle to berepaired, information (e.g., parts and labor information) about repairsmade to the vehicle to address the customer complaint (and perhaps forother reasons), and information about other vehicles that were similarlyrepaired.

For example, if a customer complains that the front brakes of a 2008Honda Civic are squeaky, electronic authoring tool software 110 can beused to enter and perhaps modify the complaint and vehicularinformation. In this example, the complaint information could be “Frontbrakes squeak” and the vehicular information could provide descriptiveinformation about a vehicle-under-repair; e.g., year of manufacture,manufacturer name, model name, owner name(s), vehicle information number(VIN), license plate number information, engine size and/or otheridentification information, and/or other information about thevehicle-under-repair. Modifications to entered information performed byelectronic authoring tool software 110 (or components thereof) caninclude, but are not limited to, correction of misspellings in enteredinformation, replacement of entered information by preferred terminologyrelated to the entered information, reordering of entered information,addition of more information (e.g., one or more words, images, sounds)to entered information, presentation of prompts intended to invokeadditional entered information, and perhaps other changes to enteredinformation.

Then, the personnel performing the repair notice both that the frontbrakes need servicing and further that the rear brakes requireservicing, and so reasons for repairs could be entered and/or modifiedusing electronic authoring tool software 110, where the reasons forrepairs can include reasons for repairing both the front and rear brakesof the vehicle. Electronic authoring tool software 110 can also be usedto enter and/or modify information about parts, labor, related costsand/or other items (e.g., environmental fees, taxes,additional/auxiliary parts used, name(s) of personnel performing therepair) for the repair.

Upon completion of the repair, any non-entered data about the repair canbe entered (and perhaps modified) using electronic authoring toolsoftware 110. Electronic authoring tool software 110 can be used togenerate one or more repair orders related to the completed repair. Therepair order(s) can include some or all of the entered and/or modifiedinformation, as well as additional information including, but notlimited to, information about commonly replaced parts and/or commonlyperformed labor codes for the same or similar repairs, additionalreplaced parts and/or additionally performed labor codes for the same orsimilar repairs, and images and/or sounds related to the performedrepair. Once generated, electronic authoring tool software 110 canoutput and/or save the generated repair order(s) as one or moredisplays, printouts, electronic communications, and/or electronicdocuments (e.g., e-mails, files, text messages with embedded links). Inother examples, electronic authoring tool software 110 can perform more,fewer, and/or different functions related receiving, modifying, and/oroutputting repair-related information.

FIG. 1A shows that electronic authoring tool software 110 can includeontology/taxonomy logic 112, system selector 120, symptom selector 122,condition selector 124, description selector 126, speed selector 128,spatial selector 130, imagery selector 132, audio selector 134,ontology/ontologies 140, taxonomy/taxonomies 142, component selector150, test result selector 152, and repair order display generator (RODG)160. In other embodiments, computing device 100 and/or electronicauthoring tool software 110 can include more, fewer, and/or differentcomponents than shown in FIG. 1A. Electronic authoring tool software 110can coordinate activities performed by components of electronicauthoring tool software 110; e.g., ontology/taxonomy logic 112,selectors 120, 122, 124, 126, 128, 130, 132, 134, 150, 152,ontology/ontologies 140, taxonomy/taxonomies 142, and repair orderdisplay generator 160.

Electronic authoring tool software 110 can include ontology/taxonomylogic 112 to process entered information and perhaps other informationusing one or more ontologies 140 and/or one or more taxonomies 142.Selectors of electronic authoring tool software 110 can be used toselect data, such as attributes and/or templates, from one or moreontologies 140 and/or one or more taxonomies 142. For example,respective system selector 120, symptom selector 122, condition selector124, description selector 126, speed selector 128, spatial selector 130,imagery selector 132, audio selector 134, component selector 150, andtest result selector 152, can select data from one or more ontologies140 and/or one or more taxonomies 142 related to respective systems,symptoms, conditions, descriptions, speeds, spaces and/or descriptionsof spaces, images, audio, components, and test results.

A selector can select attributes and/or templates, from one or moreontologies 140 and/or one or more taxonomies 142 using one or moreselection techniques. A first selection technique involves a selectorprovided with an input SEL_IN that includes a string of characters, andthe selector can search one or more ontologies 140 and/or one or moretaxonomies 142 to determine if the string represented by SEL_IN is foundin one or more templates and/or one or more attributes. In someembodiments, the selector can receive additional inputs requestingparticular information to be provided based on the contents of SEL_IN.The additional inputs can be used to request information based on thecontents of SEL_IN including, but not limited to associated attributes,attribute groups, templates, text, audio, static/still imagery, andmoving/video imagery. For example, SEL_IN can include the word “squeal”and additional inputs can request information about attributesassociated with SEL_IN. In response, the first selection technique candetermine and provide information about a noise descriptor attribute anda symptom audio attribute related to SEL_IN. Then, the first selectiontechnique can receive an additional request related to the same SEL_INwith an additional input requesting audio related to SEL_IN. Inresponse, the first selection technique can determine and provide audioinformation, such as an audio file or reference thereof, related to thesymptom audio attribute for “squeak”.

A second selection technique is to compare SEL_IN with one or moreattributes to determine if SEL_IN is a properly spelled word (or words)or is a misspelled word (or words). In some embodiments, at least thesecond selection technique can, in addition comparing SEL_IN to one ormore attributes, also search a dictionary to determine if a word (orwords) in SEL_IN are spelled correctly and/or apply stemming rules todetermine if a word (or words) in SEL_IN are properly spelled and/orutilize proper suffixes. A third selection technique is to apply one ormore grammatical and/or syntactic rules to determine if SEL_IN isproperly expressed grammatically and syntactically or is improperlyexpressed grammatically and/or syntactically. A fourth selectiontechnique is to compare one or more words in SEL_IN to one or morepreferred terms stored in one or more ontologies 140 and/or one or moretaxonomies 142 to determine if the one or more words in SEL_IN includepreferred terms, non-preferred terms, and/or terms that are neitherpreferred or non-preferred (e.g., terms not related to attributes and/ortemplates in one or more ontologies 140 and/or one or more taxonomies142).

A fifth selection technique is to apply one or more other selectiontechniques to determine differences in SEL_IN with respect to acanonical searching representation; that is, a standard representationof words usable for searching for attributes and/or templates, updateSEL_IN to resolve the differences between SEL_IN and the canonicalsearching representation, and subsequently search for the updated SEL_INin one or more ontologies 140 and/or one or more taxonomies 142 in anattempt to find one or more attributes and/or templates. The one or moreother selection techniques can be used to determine differences from thecanonical searching representation, such as determining misspelledword(s) in SEL_IN, improperly expressed grammatically and/orsyntactically word(s) in SEL_IN, and/or non-preferred word(s) in SEL_IN.Then SEL_IN can be updated to fit the canonical searchingrepresentation; e.g., any misspelled words in SEL_IN can be correctlyspelled, improperly expressed wording in SEL_IN can be properlyexpressed, and non-preferred terms in SEL_IN can be replaced withpreferred terms.

The updates to SEL_IN can be based on user input and/or programmaticallyperformed based on one or more canonical-searching-representation rulesto update SEL_IN to fit the canonical searching representation. Thesecanonical-searching-representation rules can include, but are notlimited to, rules for:

-   -   invoking other selection techniques to update SEL_IN, which can        include specifying an ordering of invocation of the other        selection techniques (e.g., use the second selection technique        before using the first selection technique),    -   reorganizing words in SEL_IN to be in a canonical order; e.g.,        nouns before verbs,    -   removing words in SEL_IN unlikely to improve the search (e.g.,        words such as “a”, “an”, “the”),    -   replacing numeric terms with corresponding numbers (e.g.,        replace “nine” with “9”), and    -   updating SEL_IN on a character-by-character basis to improve        searching (e.g., convert all characters to upper or lower case,        remove excess spaces and/or tabs).

After SEL_IN is updated, the fifth selecting technique can search one ormore ontologies 140 and/or one or more taxonomies 142 in an attempt tofind one or more attributes and/or templates using the updated SEL_IN;for example, the fifth selecting technique can be provided the updatedSEL_IN to the first selecting technique to search for attributes and/ortemplates. Other selection techniques for use by selector(s) and otherexamples related to the herein-described selection techniques arepossible as well.

Repair order display generator 160 can be used to generate one or morerepair orders that can describe one or more vehicular repairs. Oncegenerated, repair orders can be output and/or saved by computing device100, electronic authoring tool software 110, and/or repair order displaygenerator 160 as one or more displays, printouts, electroniccommunications, and/or electronic documents.

FIG. 1B is a block diagram showing relationships between one or moreontologies 140 and one or more taxonomies 142, in accordance with anembodiment. Generally speaking, taxonomies can include information aboutsingle attributes and ontologies can include information about conceptsspecified using one or more attributes. That is, ontologies can includeinformation describing multi-attribute concepts and relationships thatcan be more complex than the single-attribute concepts that can bedescribed using taxonomies.

In the example shown in FIG. 1B, one or more ontologies 140 includerepair order ontology 140 a, vehicle information ontology 140 b, partsand labor ontology 140 c, diagnosis ontology 140 d, commonly replacedparts (CRP) graph ontology 140 e, and additional replaced parts (ARP)ontology 140 f. Repair order ontology 140 a can relate concepts relatedto repair orders, such as vehicle information-related concepts relatedusing vehicle information ontology 140 b, parts and labor-relatedconcepts related using parts and labor ontology 140 c, diagnosis-relatedconcepts related using diagnosis ontology 140 d, commonly relatedparts-related concepts related using commonly replaced parts graphontology 140 e, additionally replaced parts-related concepts relatedusing additional replaced parts (ARP) ontology 140 f, and perhaps otherconcepts; e.g., graph-related concepts, audio-related concepts, otherconcepts related to repair orders.

In the example shown in FIG. 1B, one or more taxonomies 142 includevehicle information taxonomy 142 a, parts and labor taxonomy 142 b,diagnosis taxonomy 142 c, commonly replaced parts taxonomy 142 d, andadditional replaced parts taxonomy 142 e. For this example, vehicleinformation ontology 140 b can specify vehicle information-relatedconcepts using attributes specified by vehicle information taxonomy 142a, parts and labor ontology 140 c can specify parts and labor-relatedconcepts using attributes specified by parts and labor taxonomy 142 b,diagnosis ontology 140 d can specify diagnosis-related concepts usingattributes specified by parts and labor taxonomy 142 c, commonlyreplaced parts ontology 140 e can specify commonly replacedparts-related concepts using attributes specified by commonly replacedparts taxonomy 142 d, and additional replaced parts ontology 140 f canspecify additional replaced parts-related concepts using attributesspecified by additional replaced parts taxonomy 142 e.

In other examples, the one or more ontologies 140 can include more,fewer, and/or different ontologies than shown in FIG. 1B and/or one ormore taxonomies 142 can include more, fewer, and/or different taxonomiesthan shown in FIG. 1B. In still other examples, one-to-one mappingsbetween ontologies 140 and taxonomies 142 are not used; e.g., ontologies140 can include one ontology, such as repair order ontology 140 a whilemultiple taxonomies are used in taxonomies 142, multiple ontologies canbe used as ontologies 140 while one taxonomy; e.g., a commonrepair-related taxonomy specifying all repair-related attributes used byontology/taxonomy logic 112, can be used, or multiple ontologies andmultiple taxonomies can be used that do not have one to one mappings;e.g., the taxonomies shown in FIG. 1B can be replaced by a componentstaxonomy, a labor-related taxonomy, and an “other attributes” taxonomy.Many other examples are possible as well.

As an example use case, ontology/taxonomy logic 112 can receive anentered term, such as “engin” and provide the term to ontology/taxonomylogic 112. Ontology/taxonomy logic 112 can receive the term “engin” andselect an ontology from among one or more ontologies 140 and/or select ataxonomy from among one or more taxonomies 142 related to the enteredterm “engin”. In some embodiments, ontology/taxonomy logic 112 can useone or more selectors, such as system selector 120 and/or componentselector 150, to select one or more taxonomies that can include enteredterm “engin”, such as one or more taxonomies related to vehicularsystems and/or components.

Upon selection of ontologies and/or taxonomies related to the enteredterm, ontology/taxonomy logic 112 can process and perhaps modify theentered term using the selected ontologies and/or taxonomies. In thisexample, ontology/taxonomy logic 112 can use a taxonomy such as vehicleinformation taxonomy 142 a, parts and labor taxonomy 142 b, or diagnosistaxonomy 142 c to determine that the entered term “engin” is likely tobe a misspelled version of the attribute “engine”. Then,ontology/taxonomy logic 112 can modify the entered term “engin” to bethe properly spelled term “engine”.

In a related example, ontology/taxonomy logic 112 can receive anotherentered term “motor” and provide the term to ontology/taxonomy logic112. In some embodiments, ontology/taxonomy logic 112 can use one ormore selectors, such as system selector 120 and/or component selector150, to select one or more taxonomies that can include entered term“motor” and related preferred terms, such as one or more taxonomiesrelated to vehicular systems and/or components.

In this example, ontology/taxonomy logic 112 can use a taxonomy such asvehicle information taxonomy 142 a, parts and labor taxonomy 142 b, ordiagnosis taxonomy 142 c to determine that the entered term “motor” islikely to be a non-preferred term whose related preferred term is“engine”, and so modify the entered term “motor” to be the preferredterm “engine”. Continuing this example, the entered term “motor” can bepart of an entered set of terms “motor needs 2 b rebuilt”. Afterreplacing “motor” with “engine” and making other textual corrections(e.g., replacing “2” with “to”, replacing “b” with “be”, and replacingthe non-preferred term “rebuilt” with the preferred term “overhauled”),the modified set of terms can be “engine needs to be overhauled”.

To obtain additional information about an unspecified attribute, such asa diagnosis-related attribute, ontology/taxonomy logic 112 can requestelectronic authoring tool software 110 to generate a request, such as auser prompt or database query, to specify the currently-unspecifieddiagnosis-related attribute. In this example, electronic authoring toolsoftware 110 can use a user interface to prompt repair personnel toprovide information about the diagnosis-related attribute, and canreceive a second set of terms “the head gasket is blown”.

Electronic authoring tool software 110 can the provide the second set ofterms ontology/taxonomy logic 112 as a specification of thediagnosis-related attribute, and ontology/taxonomy logic 112 can updatethe template with a modified version of the second set of terms aftermodifying the non-preferred term “blown” with a preferred term“defective” and updating the preferred term “overhauled” to change theterm's ending to fit the template as the updated term “overhauling”.After making these changes, the updated template can read “The enginerequires overhauling due to the head gasket being defective”.Ontology/taxonomy logic 112 can provide the updated template toelectronic authoring tool software 110 and/or computing device 100 forpresentation, review, and perhaps additional input from the repairpersonnel.

FIG. 2A is a diagram of electronic authoring tool software 110, inaccordance with an embodiment. Ontology/taxonomy logic 112 of electronicauthoring tool software 110 can communicate with one or more selectors,such as system selector 120, symptom selector 122, condition selector124, descriptor selector 126, speed selector 128, and spatial selector130 as shown in FIG. 2A.

Ontology/taxonomy logic 112 can communicate with a selector to requestinformation about one or more attributes associated with the selectorand, in response, receive the requested information from the selector.For example, if electronic authoring tool software 110 requestsinformation about an attribute, such as a <condition> attribute,electronic authoring tool software 110 can generate and communicate arequest about the <condition> attribute to ontology/taxonomy logic 112.In response to the request about the <condition> attribute,ontology/taxonomy logic 112 can determine a selector that is related tothe <condition> attribute, such as condition selector 124, and requestinformation about the <condition> attribute from condition selector 124.

Condition selector 124 can provide the requested information toontology/taxonomy logic 112, where the information can include a listingof one or more attributes, one or more descriptions about one or moreattributes, one or more preferred and/or non-preferred terms related toone or more attributes, and/or other information about attributesassociated with condition selector 124. In this example, the requestedinformation about the <condition> attribute involves a listing of allpossible attributes that could be a <condition> attribute that include aword related to “heat”. Condition selector 124 can examine conditionattributes 230 to find all attributes that include the string “heat” tofind a “Heater On” attribute. In some embodiments, condition selector124 can look for attributes with strings similar to and/or related tothe string “heat” and additionally find the “When Hot” attribute. The,condition selector 124 can generate a listing of the “Heater On” andperhaps the “When Hot” attribute(s) and provide the listing toontology/taxonomy logic 112, which in turn can provide the listing ofthe “Heater On” and perhaps the “When Hot” attribute(s) to electronicauthoring tool software 110.

FIG. 2A shows that system selector 120 can be associated with systemgroups 210. System groups 210 include system groups related to vehicularsystems that include system groups for: an “Engine”, a “Transmission”,an “ABS” or Automatic Braking System, “Brakes”, “Windows”, “Components”,a “HVAC” system or Heating, Ventilating, and Air Conditioning system,and “Fluids”. For each system group of system groups 210, additionalattributes and/or groups can be included that are related to the systemgroup; e.g., the “Engine” group can have attributes and/or groupsrelated to a fuel system, an “Exhaust System”, a “Timing” system, etc.

Symptom selector 122 can be associated with symptom groups 220, whichcan include “Smell”, “Engine”, “Trans[mission]”, “HVAC”, “Brakes”, and“Color” symptom groups as indicated in FIG. 2A. Each symptom group ofsymptoms groups 220 can be associated with symptom attributes of symptomattributes 222.

FIG. 2A also shows that: the “Smell” symptom group can be associatedwith “Burning”, “Sweet”, “Acrid”, “Oily”, and “Mildew” symptomattributes of symptom attributes 222; the “Engine” symptom group can beassociated with “Not Starting”, “Runs Rough”, and “Hesitates” symptomattributes; the “Trans[mission]” symptom group can be associated withthe “Not Shifting” and “Hard to Shift” symptom attributes; the “HVAC”symptom group can be associated with the “Inoperative” and “Makes Noise”symptom attributes, the “Brakes” symptom group can be associated withthe “Vibrating”, “Noisy”, and “Inoperative” symptom attributes; and the“Color” symptom group can be associated with the “Fluid” and “Smoke”symptom attributes of symptom attributes 222. In some examples, oneattribute can be associated with multiple attribute groups; e.g., thesymptom attribute “Inoperative” is associated with both the “HVAC’ and“Brakes” symptom groups. In other examples, more, fewer, and/ordifferent symptom groups 220 and/or symptom attributes 222 can beassociated with symptom selector 122.

Condition selector 124 can be associated with condition attributes 230,which include condition-related attributes such as “When Cold”, “WhenHot”, “When Raining”, “Stopping”, “Turning”, “Over Bumps”,“Accelerating”, “Decelerating”, “Backing Up”, “Heater On”, “A/C On”which can abbreviate an “air conditioner on” condition, “In Neutral”,“Uphill”, and “Downhill”, as shown in FIG. 2A. In other examples, more,fewer, and/or different condition attributes 230 can be associated withcondition selector 124.

Descriptor selector 126 can be associated with description groups 240.Each description group can include one or more description attributes ordescriptions 242. For example, description groups 240 include a“Freq[uency]” group of descriptions and a “Noise” group of descriptions.FIG. 2A shows that the “Freq[uency]” description group includes“Intermittent” and “Regular” descriptions of descriptions 242, and the“Noise” group of descriptions includes “Squeal”, “Grind”, “Growl”,“Clunk”, and “Rattle”.

Speed selector 128 can be associated with speed attributes 244, whichinclude speed-related attributes such as “City Speeds”, “HighwaySpeeds”, “Idle”, “High Speed”, “Low Speed” as shown in FIG. 2A. In otherexamples, more, fewer, and/or different speed attributes 244 can beassociated with speed selector 128.

Spatial selector 130 can be associated with spatial attributes 232,which include space-related attributes such as “Left”, “Right”, “Front”,“Rear”, “Right Front”, “Right Rear”, “Left Front”, “Left Rear”, “Under”,“Over”, “Engine”, “Trunk”, and “Dashboard”, as shown in FIG. 2A. Inother examples, more, fewer, and/or different spatial attributes 232 canbe associated with spatial selector 130.

Selectors can operate on a hierarchy or other organization of attributesthat can include individual attributes and groups of attributes. Forexample, spatial selector 130 can operate on one unnamed group ofspatial attributes shown in FIG. 2A as spatial attributes 232. Asanother example, system selector 120 can operate on groups of attributesshown in FIG. 2A as system groups 210. As a third example, symptomselector 122 can operate on groups of attributes shown in FIG. 2A assymptom groups 220 which in turn include individual attributes shown inFIG. 2A as symptom attributes 222. In other examples not shown in FIG.2A, a selector can apply one or more selection techniques to both groupsand individual attributes, operate on groups of groups (of groups . . .) of attributes, and/or operate on different organizations of attributesand groups of attributes than the hierarchical organizations shown inFIG. 2A.

In some embodiments, attributes can be related to other attributes. Asone example, a group of attributes can be considered to be related toeach other as being part of the same group. As another example, the“Rattle” description attribute can be related to an audio attribute witha recording of a (typical) rattle sound and/or an image of a componentthat typically makes a rattle sound. As another example, one attributecan represent a non-preferred and/or misspelled term that is related toa preferred and/or correctly spelled term; e.g., an attribute for anon-preferred term “motor” and/or an attribute for a misspelled term“engin” can be related to an attribute for the preferred, properlyspelled term “engine”. Many other examples of attribute relationshipsare possible as well.

FIG. 2B is another diagram of electronic authoring tool software 110, inaccordance with an embodiment. FIG. 2B shows that ontology/taxonomylogic 112 of electronic authoring tool software 110 can be associatedwith selectors 120, 122, 124, 126, 128, and 130 shown and discussedabove in more detail in the context of FIG. 2A, and can be associatedwith audio selector 132 and video selector 134.

Imagery selector 132 can be associated with imagery groups 262. Eachimagery group can include one or more imagery attributes 264. Forexample, imagery groups 262 include a “Data Images” group of imageryattributes, “Static Images” group of imagery attributes, and “VideoImages” group of imagery attributes. FIG. 2B shows that the “DataImages” group includes “Area Chart”, “Bar Chart”, “Bubble Chart”, “PieChart”, “Line Graph”, “Cumulative Line Graph”, and “Scatter Plot”imagery attributes 264. The imagery attributes in the “Data Images”group can include attributes indicating techniques to specify, describe,and/or display data sets; e.g., the “Bar Chart” imagery attribute canindicate that a bar chart technique can be used to display a data set.Such imagery attributes can include attributes that specifysub-attributes of the technique; e.g., for the “Bar Chart” imageryattribute, sub-attributes can include, but are not limited to,sub-attributes related to the data set displayed using a bar chart,number of bars, colors of bars, axis labels, orientation (e.g.,horizontal, landscape, vertical, portrait), font sizes, and labelsrelated to the bar chart.

FIG. 2B shows that the “Static Images” group can include imageattributes indicating individual and/or groups of static images (e.g.,electronic photographs, drawings, etc.). FIG. 2B shows that the “StaticImages” group includes “Customer Vehicle Image” imagery attribute ofimagery attributes 264 of that are related to images of customervehicles, “System Image” imagery attribute related to images of systemsof vehicles (e.g., engines, transmission, brakes), “System ComponentImage” imagery attribute related to images of vehicle components (e.g.,air filters, gears, calipers), “Logo Image” imagery attribute related toone or more logos related to vehicle repair (e.g., a logo of a repairfacility, logos of component suppliers), “Background Image” imageryattribute related to background images (e.g., backgrounds of repairorders), and “Other Images” imagery attribute related to other staticimages. FIG. 2B shows that the “Video Images” group can include imageryattributes of imagery attributes 264 indicating individual and/or groupsof video imagery (i.e., moving imagery), where the. “Video Images”imagery group can include “Customer Vehicle Video” imagery attributerelated to videos of customer vehicles, “System Video” imagery attributerelated to videos of systems of vehicles, “System Component Image”imagery attribute related to videos of vehicle components and “OtherVideo” imagery attribute related to other videos.

Audio selector 134 can be associated with audio groups 266. Each audiogroup can include one or more audio attributes 268. For example, imagerygroups 266 include a “Symptom” group of audio attributes, “ConditionAudio” group of audio attributes, and “Descriptive Audio” group of audioattributes. FIG. 2B shows that the “Symptom Audio” group includes“Squeal Audio” audio attribute related to audio of squealingsounds/squeal symptoms, “Grind Audio” audio attribute related to audioof grinding sounds/grind symptoms, “Growl Audio” audio attribute relatedto audio of growling sounds/growl symptoms, “Clunk Audio” audioattribute related to audio of clunking sounds/clunk symptoms, and“Rattle Audio” audio attribute related to audio of rattlingsounds/rattle symptoms of audio attributes 268.

FIG. 2B shows that the “Condition Audio” group includes “AcceleratingAudio” audio attribute related to audio recording and/or aboutaccelerations and “Decelerating Audio” audio attribute related to audiorecording and/or about decelerations of audio attributes 268. FIG. 2Balso shows that the “Descriptive Audio” group includes “Engine NotStarting Audio” audio attribute related to audio of engines failing tostart/turn-over, “Engine Runs Rough Audio” audio attribute related toaudio of engines operating roughly, “Engine Hesitates Audio” audioattribute related to audio of engines operating in a hesitant fashion,“Trans. Not Shifting Audio” audio attribute related to audio oftransmissions failing to shift, “Trans. Hard to Shift Audio” audioattribute related to audio of transmissions hesitating to shift, “HVACMakes Noise Audio” audio attribute related to HVAC system noises, and“Brake Noise Audio” audio attribute related to audio of brake noises ofaudio attributes 268. In some embodiments, electronic authoring toolsoftware 110 can be associated with more, fewer, and/or differentselectors than shown in FIG. 2A and/or FIG. 2B.

FIG. 2C shows example ontology 140 a that includes templates 270, 272,274, 276. Each template shown in FIG. 2C shows an ordering thatspecifies how attributes can be entered and/or displayed for aparticular conceptual item using electronic authoring tool software 110.For example, sentence template 270 indicates that a sentence (an exampleof a conceptual item) can include, in order, a symptom attribute, adescription attribute, a spatial attribute, a system attribute, acondition attribute, and a speed attribute. As another example, sentencetemplate 272 indicates that a sentence can include, in order, a spatialattribute, a system attribute, a description attribute, a symptomattribute, a condition attribute, and a speed attribute.

Continuing this example, example values can include: “burning smell” forthe symptom attribute, “regular” for the description attribute, “front”for the spatial attribute, “radiator of the engine” for the systemattribute, “when hot” for the condition attribute, and “at any speed”for the speed attribute. Then, a sentence that can be generated byelectronic authoring tool software 110 and/or ontology/taxonomy logic112 using sentence template 270 can be “The customer noticed a burningsmell on a regular basis from the front of the vehicle and/or theradiator of the engine that occurred when hot and/or when the vehiclewas operated at any speed” where the bold terms shown above representexample predetermined attribute values that can be inserted intotemplate 270 to replace variable attribute values.

Further, a different sentence that can be generated by electronicauthoring tool software 110 and/or ontology/taxonomy logic 112 usingsentence template 272 can be “The front of the vehicle and/or theradiator of the engine had a regular burning smell that occurred whenhot and/or when the vehicle was operated at any speed” where the boldterms are example attribute values that can be inserted into template272. Many other example sentences and templates are possible as well.

Multiple templates can exist and be used for the same conceptual item.For example, FIG. 2C shows two sentence templates 270, 272 for asentence and shows two repair order templates 274, 276 for a repairorder (another example conceptual item). If multiple templates exist fora particular conceptual item, then the templates can vary betweenorderings, numbers, and/or types of attributes, leading to differentspecific conceptual items. For example, sentence templates 270, 272 bothrefer to the same six attributes—symptom, description, spatial, symptom,condition, and speed attributes—but order the six attributesdifferently. As another example, repair order templates 274, 276 havedifferent numbers and types of attributes—both repair order templates274, 276 order a vehicle information attribute before a cause attribute,and order the cause attribute before a parts and labor attribute. Repairorder template 274 includes only those three attributes—vehicleinformation, cause, and parts and labor attributes. However, repairorder template includes six attributes ordered as vehicle information,cause, diagnosis, parts and labor, commonly replaced parts graph, andadditional related parts attributes. In other examples, ontology 140 acan include more, fewer, and/or different templates and/or templatesthat use different wordings.

FIG. 2D shows example ontology 140 b expressed as a table of attributegroup values 280 and attribute values 282. Ontology 140 b can relateattribute groups and attributes. FIG. 2D shows that ontology 140 bincludes:

-   -   1. first and second non-heading rows indicating a “Fluid”        attribute group includes “Coolant” and “Fuel” attributes,    -   2. a third non-heading row indicating a “Freq.” attribute group        includes “Intermittent” attribute,    -   3. fourth and fifth non-heading rows indicating a “Speed”        attribute group includes “High Speed” and “Low Speed”        attributes,    -   4. sixth, seventh, and eighth non-heading rows indicating a        “Spatial” attribute group can include “Front”, “Inside”, and        “Left” attributes,    -   5. ninth, tenth, eleventh, and twelfth non-heading rows        indicating a “System” attribute group can include “Air        Conditioning”, “Brakes”, “Door Lock”, and “Window” attributes,        and    -   6. thirteenth, fourteenth, fifteenth, and sixteenth non-heading        rows indicating a “Condition” attribute group can include        “Accelerating”, “Over Bumps”, “Hot”, and “Stopping” attributes.

Using ontology 140 b and related tables, relationships between attributegroups and attributes such as the relationships shown in FIGS. 2A and 2Bcan be specified, as well as other relationships between attributegroups and attributes. More, fewer, and/or different attribute groups,attributes, and/or relationships between attribute groups and attributescan be specified and/or expressed using ontology 140 b.

Example User Interfaces Related to Repair Orders and CorrespondingOntology/Taxonomy Logic

FIGS. 3A-3D depict example views of user interface (UI) 310 of computingdevice 100 used for entering data for a repair order, such as avehicular repair order, in accordance with an embodiment. For example,user interface 310 can be a graphical user interface. In the specificexample shown in FIGS. 3A-3D, user interface 310 is a graphical userinterface for electronic authoring tool software 110. Then, userinterface 310 can be used to enter, modify, display, and/or update datarelated to repair orders including, but not limited to, data related tovehicle information, (customer) complaints, causes for (customer)complains, repairs, parts and labor, commonly replaced parts, and/oradditionally replaced parts.

FIG. 3A shows that user interface 310 includes selection type display312, selection indication display 314, system selections 316 includingselection 318, text entry region 320, and buttons 322, 330, 332, 334. Inparticular, user interface 310 can be used to enter (customer) complaintdata as text via text entry region 320. In other embodiments, userinterface 310 can be used to enter data via other modalities, such asimages, sounds, etc.; e.g., user interface 310 can enable uploading ofsounds, images, videos, etc. related to repair orders.

While text is entered in text entry region 320, electronic authoringtool software 110 and/or user interface 310 can process entered text,generate displays, and/or modify the entered text. The text can bemodified based on one or more templates associated with one or moreontologies, such as templates shown associated with ontology 140 a ofFIG. 2C. The template can be used to arrange text according to anordering of attributes specified by the template. Also, as the templatecan include attributes, computing device 100, electronic authoring toolsoftware 110, and/or user interface 310 can use the template todetermine attributes and/or attribute groups related to the entered textand modify the entered text based on the determined attributes and/orattribute groups.

For example, FIG. 3A shows that the text entered in text entry region320 currently reads as “Customer reports that the”. In this example,electronic authoring tool software 110, ontology/taxonomy logic 112,and/or user interface 310 can select a template. The template can beassociated with the entered text can indicate that text is to be enteredrelated to a system attribute; e.g., the template can have an orderingindicating that a variable system-related attribute is to be entered.Then, as a system-related attribute is to be provided, electronicauthoring tool software 110 can instruct user interface 310 to displayselection type display 312 which reads “Select Primary System” to promptentry of the system attribute. To aid and/or prompt entry of the systemattribute, electronic authoring tool software 110 can instruct userinterface 310 to display system selections 316 showing example systemattributes, such as “Body”, “Brakes”, “Engine”, “HVAC”, “Infotainment”,and “Transmission.”

User interface 310 can receive input to make a selection of systemselections 316; e.g., mouse input, keyboard input, touch input. In theexample shown in FIG. 3A, selection indication 314 and selection 318both indicate that “HVAC” is chosen from among system selections 316.User interface 310 can accept additional input to change the selection,accept the selection, and/or make a new selection. In one example, anacceptance input, such as a touch of user interface 310 on the displayed“HVAC” or on accept selection button 322, a mouse click on the displayed“HVAC”, or pressing of a key (e.g., an enter key) can accept the “HVAC”selection. In another example, a second input can change and/or make anew selection that differs from selection 318, such as a touch or mouseclick on a different selection of system selections 316, scroll-wheelinput, and/or entry of text in text entry region 320.

Buttons 330, 332, and 334 can control aspects of user interface 310.Modify text button 330 can be used to explicitly request modification oftext. For example, if text of “A/C” were entered using text entry region320, selection of modify text button 330 can be used to accept textentered in text entry region 320 and determine one or more templatesassociated with the accepted text; e.g., by using ontology/taxonomylogic 112 to search one or more ontologies for templates associated withthe accepted text. After determining the template(s), the accepted textcan be modified, perhaps based on the template(s); e.g., spelling errorsin the accepted text can be corrected, the accepted text can bereordered to conform to an ordering of wording/attributes specified bythe template(s), words can be added, deleted, and/or changed to theaccepted text to conform to wording specified by the template(s),non-preferred terms for attributes specified in the template(s) can befound in the accepted text and replaced with preferred terms. Othertechniques for modifying entered text are possible as well.

After the text has been modified, the modified text can then bedisplayed using user interface 310; e.g., the modified text can replacethe entered text in text entry region 320. Continuing this example, theentered text includes the term “A/C”. Upon acceptance of the enteredtext, electronic authoring tool software 110; e.g., ontology/taxonomylogic 112 can find a template related to the entered text can be foundin an ontology that includes a system attribute. Preferred terms andnon-preferred terms related to the system attribute and the entered term“A/C” can be searched in one or more ontologies and/or taxonomies. Then,electronic authoring tool software 110; e.g., ontology/taxonomy logic112 can determine that the entered text “A/C” is a non-preferred termfor an air conditioning system with a related preferred term of “HVAC”.Then, electronic authoring tool software 110 can replace thenon-preferred term “A/C” in the accepted text with the preferred term“HVAC” and can then instruct user interface 310 to display the modifiedtext with the preferred term “HVAC”.

Accept text button 332 can be used to accept text displayed in textentry region 320. In some embodiments, once text is accepted, then theaccepted text can be modified using the techniques discussed aboveregarding modify text button 330. In other embodiments, text acceptedafter accept text button 332 is not modified by electronic authoringtool software 110. Exit button 334 can be used to close user interface310 and perhaps end execution of electronic authoring tool software 110on computing device 100.

FIG. 3B shows user interface 310 updated after additional text has beenentered in comparison to the text shown in FIG. 3A. In particular, FIG.3A shows text in text entry region 320 of “Customer reports that the”and FIG. 3B shows that text in text entry region 320 of “Customerreports that the HVAC has a smell”.

In this example, a template associated with the entered text of FIG. 3Bcan indicate that text being entered relates to a condition attribute.Then, electronic authoring tool software 110 can instruct user interface310 to display selection type display 342 with “Select PrimaryCondition” and to present condition selections 346 that include“Inoperative”, “Noise”, “Leak”, and “Odor”. In this example, electronicauthoring tool software 110 can use ontology/taxonomy logic 112 toprocess the text entered in text entry region 320 that includes the word“smell”, determine that “smell” is a non-preferred term related to apreferred term “odor” for a condition attribute, and suggest selection348 of the preferred term “odor”. In the example shown in FIG. 3B, bothselection 348 and selection indication 344 indicate that “Odor” ischosen from among system selections 346.

The example continues with the term “odor” being accepted as part of thetext entered using text entry region 320. Upon acceptance of the term“odor”, the text in text entry region 320 can be modified to replace thewords “a smell” with the words “an odor”.

FIG. 3C shows user interface 310 updated after additional text has beenentered in comparison to the text shown in FIG. 3B. In particular, FIG.3B shows text in text entry region 320 of “Customer reports that theHVAC has a smell” and FIG. 3C shows text in text entry region 320 of“Customer reports that the HVAC has an odor from the front”.

In this example, a template associated with the entered text of FIG. 3Ccan indicate that text being entered relates to a spatial attribute.Then, electronic authoring tool software 110 can instruct user interface310 to display selection type display 352 with “Select SpatialQualifier(s)” and to present spatial selections 356 that include “Left”,“Right”, “Front”, and “Rear”. In this example, electronic authoring toolsoftware 110 can use ontology/taxonomy logic 112 to process the textentered in text entry region 320 that includes the word “front”determine that “front” is a preferred term for a spatial attribute, andsuggest selection 358 of the preferred term “front”. In the exampleshown in FIG. 3C, both selection 358 and selection indication 354 bothindicate that “Front” is chosen from among spatial selections 356.

The example continues with the term “front” being accepted as part ofthe text entered using text entry region 320.

FIG. 3D shows user interface 310 updated after additional text has beenentered in comparison to the text shown in FIG. 3C. In particular, FIG.3C shows text in text entry region 320 of “Customer reports that theHVAC has an odor from the front” and FIG. 3D shows that text in textentry region 320 of “Customer reports that the HVAC has an odor from thefront side vent.”

In this example, a template associated with the entered text of FIG. 3Dcan indicate that text being entered relates to a component attribute,such as a component of the previously-selected HVAC system. Then,electronic authoring tool software 110 can instruct user interface 310to display selection type display 362 with “Select Component(s) and topresent component selections 366 that include “Duct”, “Vent”, “CenterVent”, and “Side Vent”. In this example, electronic authoring toolsoftware 110 can use ontology/taxonomy logic 112 to process selection368 of “Side Vent” (e.g., a selection made using a finger press, keypress, or mouse click) to insert corresponding text of “side vent” intothe text displayed in text entry region 320. In the example shown inFIG. 3D, selection indication 364 indicates that “SIDE VENT” has beenchosen from among components 366. The example continues with the term“side vent” being added to the text entered using text entry region 320.

In other examples, user interface 310 can allow multiple selections fromcomponent selections 366 or other displayed selections (e.g., systemselections 316, condition selections 346, spatial selections 356). Inthese examples, electronic authoring tool software 110 can make multiplemodifications to entered text and/or other data based on the multipleselections. For a particular example related to FIG. 3D, if there was acomplaint of a smell coming from both a front side vent and a centervent of an HVAC system, then both “Center Vent” and “Side Vent” can beselected from component selections 366 to make multiple modifications tothe text displayed in text entry region 320; e.g., to add the term “sidevent”, add the word “and”, and add the term “the center vent”. Theresulting text for this particular example can be “Customer report thatthe HVAC has an odor from the front side vent and the center vent”.

FIGS. 4A-4D depict example views of another user interface of acomputing device used for entering data for a repair order, inaccordance with an embodiment. The example shown in FIGS. 4A-4D involvesentry of the same text discussed above in the context of FIGS. 3A-3D,but the text is entered using user interface 410 instead of userinterface 310.

In the specific example shown in FIGS. 4A-4D, user interface 410 is agraphical user interface for electronic authoring tool software 110 thatcan be used to enter, modify, display, and/or update data related torepair orders such as discussed above in the context of user interface310.

FIG. 4A shows that user interface 410 includes text entry region 420,selections 422, 424, 426, indicator 428, and buttons 430, 432, 434, 436.In particular, user interface 410 can be used to enter (customer)complaint data as text via text entry region 420. In other embodiments,user interface 410 can be used to enter data via other modalities, suchas images, sounds, etc.; e.g., user interface 410 can enable uploadingof sounds, images, videos, etc. related to repair orders.

While text is entered in text entry region 420, electronic authoringtool software 110 and/or user interface 410 can process entered text,generate displays, and/or modify the entered text. The text can bemodified based on one or more templates associated with one or moreontologies, such as templates shown associated with ontology 140 a ofFIG. 2C. Modification of text based on one or more templates isdiscussed above in more detail in the context of user interface 310.

FIG. 4A shows that the text entered in text entry region 420 currentlyreads as “aircon” and indicator 428 of “Repair Order” indicating thatelectronic authoring tool software 110 is expecting text related torepair orders. In this example, electronic authoring tool software 110,ontology/taxonomy logic 112, and/or user interface 410 can use the textof “aircon” from text entry region 420 and locate attributes and/ortemplates that indicate the “aircon” text can be related to a system,such as an HVAC system, and/or components of the HVAC system. Then,electronic authoring tool software 110, ontology/taxonomy logic 112,and/or user interface 410 can determine the “aircon” text relates to asystem attribute. As a system attribute is or has been entered via userinterface 410, electronic authoring tool software 110 can instruct userinterface 410 to present selections related to the system attribute. Inthe example shown in FIG. 4A, user interface 410 presents three systemselections: selection 422 of “HVAC”, selection 424 of “Air conditioner”,and selection 426 of “Air Compressor”.

In the example shown in FIG. 4A, user interface 410 receives anacceptance input choosing system selection 422; e.g., mouse input,keyboard input, touch input. After receiving the acceptance input, userinterface 410 changes display of system selection 422 to have a graybackground to indicate the choice of selection 422; in other examples,other techniques, including other visual techniques, can indicate achoice of a selection. User interface 410 can accept additional input tochange the selection, accept the selection, and/or make a new selection.In one example, the acceptance input can be a touch (e.g., received viaa touch screen) of user interface 410 on system selection 422, a mouseclick on system selection 422, or pressing of a key (e.g., an enterkey). In another example, a second input can change and/or make a newselection that differs from selection 422, such as a touch or mouseclick on a different selection than selection 422, scroll-wheel input,and/or entry of text in text entry region 420.

Buttons 430, 432, and 434 can control aspects of user interface 410.Exit button 430 can be used to close user interface 410 and perhaps endexecution of electronic authoring tool software 110 on computing device100. Clear button 432 can be used to remove and/or clear text from textentry region 420. Accept button 434 can be used to enter and/or textfrom text entry region for processing by electronic authoring toolsoftware 110, ontology/taxonomy logic 112, and/or user interface 410.

In the example shown in FIG. 4A, selection of system selection 422and/or selection of accept button 434 can be used to explicitly requestmodification of text. Requesting modification of text and subsequentlymodifying text is discussed above in more detail in the context of userinterface 310. In this example, selection of system selection 422 causesmodification of the “aircon” text to be “Customer reports that theHVAC”. After the text has been modified, the modified text can then bedisplayed using user interface 410; e.g., the modified text can replacethe entered text in text entry region 420.

FIG. 4B shows user interface 410 updated after the “aircon” text of FIG.4A has been modified and displayed to be “Customer reports that theHVAC”. In this example, a template associated with the displayed text ofFIG. 4B can include that text to be entered relates to a conditionattribute. Then, electronic authoring tool software 110 can instructuser interface 410 to present indicator 448 indicating choices for“Repair Order Selection”, condition selections including conditionselection 442 of “is inoperative”, condition selection 444 of “makesnoise”, and condition selection 446 of “has an odor”. In the exampleshown in FIG. 4B, condition selection 446 is shown in gray to indicate achoice of condition selection 446 and related text of “has an odor”.

The example continues with the phrase “has an odor” being accepted aspart of the text, and the text updated to display “has an odor” in textentry region 420. After text entry region is updated, additional text of“fron” is entered using text entry region 420.

FIG. 4C shows text entry region 420 of user interface 410 updated afterthe phrase “has an odor” has been added and additional text of “fron”has been entered. In this example, a template associated with theentered text “fron” can indicate that “fron” should relate to a spatialattribute, as also shown by indicator 458 indicating choices for “RepairOrder Location”. In some embodiments, such as shown in FIG. 4C, a visualindication of a misspelled word can be used by user interface 410 toshow that a word is misspelled; in this example, user interface 410determines that the word “fron” is a misspelled word and indicates thisdetermination using italics.

Then, electronic authoring tool software 110 can instruct user interface410 to present spatial selections including spatial selection 452 of“from”, spatial selection 454 of “from the front”, and spatial selection456 of “from the left”. In the example shown in FIG. 4C, spatialselection 454 is shown in gray to indicate a choice of spatial selection454 and related text of “from the front”. After receiving the choice ofspatial selection 454, the text in text entry region can be modified toreplace “fron”. In other examples, another visual and/or other types ofindications (e.g., auditory, haptic) can be used to indicate amisspelled word. In still other examples, visual and/or other types ofindications can be used to identify text in text entry region that wouldbe modified and/or replaced by choice of a selection; e.g, identify thatthe text “fron” is to be modified/replaced by “from the front” ifspatial selection 454 is chosen.

The example continues with the “fron” being replaced with “from thefront” in text entry region 420 after spatial selection 454 is chosen.FIG. 4D shows user interface 410 updated after “from the front” hasreplaced “fron” in the text shown in FIG. 4C. The resulting text isshown in FIG. 4D as “Customer reports that the HVAC has an odor from thefront” shown in text entry region 420. Text entry region 420 also showsthe term “side vent” added to that text, further resulting in text oftext entry region 420 of “Customer reports that the HVAC has an odorfrom the front side vent.”

In this example, a template associated with the displayed text of“Customer reports that the HVAC has an odor from the front” can indicatethat text to be entered relates to a component attribute. Then,electronic authoring tool software 110 can instruct user interface 410to present indicator 460 indicating choices related to “Repair OrderComponent[s]” and component selections, which include componentselection 462 of “duct”, component selection 464 of “vent”, componentselection 466 of “center vent”, and component selection 468 of “sidevent”.

In the example shown in FIG. 4D, component selection 468 is shown ingray to indicate a choice of component selection 468 and related text of“side vent”. After receiving the choice of component selection 468, thetext in text entry region can be modified to add the words “side vent”as shown in FIG. 4D.

In other examples, user interface 410 can allow multiple selections fromcomponent selections 462-468 or other displayed selections (e.g., systemselections 422-426, condition selections 442-446, spatial selections452-456). In these examples, electronic authoring tool software 110 canmake multiple modifications to entered text and/or other data based onthe multiple selections. For a particular example related to FIG. 4D, ifthere was a complaint of a smell coming from both a front side vent anda center vent of an HVAC system, then both component selections 468 and466 (in that order) can be selected to make multiple modifications tothe text displayed in text entry region 420; e.g., to add the term “sidevent”, add the word “and”, and add the term “the center vent”. Theresulting text for this particular example can be “Customer reports thatthe HVAC has an odor from the front side vent and the center vent”.

FIG. 5A depicts an example view of a user interface of computing device100 used for displaying a repair order 500, in accordance with anembodiment. For example, the user interface for repair order 500 can beprovided by electronic authoring tool software 110 utilizing at leastrepair order display generator 160.

Repair order 500 includes vehicle information 510, diagnosis 512, andparts and labor information 514. Vehicle information 510 can includedata about a vehicle under repair. In the example shown in FIG. 5A,vehicle information 510 indicates that the vehicle under repair wasmanufactured in “2002” having a make (manufacturer), model, andsub-model respectively of “Honda”, “Civic”, and “DX”, and the vehicleunder repair includes a “1.7 L” engine. In other examples, more, less,and/or different information can be provided as vehicle information.

Diagnosis 512 can include information related to a diagnosis of thevehicle under repair, including, but not limited to, complaintinformation, cause information, and/or repair information. In theexample shown in FIG. 5A, diagnosis 512 includes complaint informationthat “The customer states the engine idles rough with A/C on” and repairinformation that an “Air control valve was checked and replaced”. Insome embodiments, complaint information and/or repair information can bemodified by electronic authoring tool software 110 prior to generationof repair order 500.

Parts and labor information 514 can include information about partsand/or labor used to fix the vehicle under repair. In the example shownin FIG. 5A, parts and labor information 514 indicates that an “Idle AirControl Valve” having part number “18011-P7C-IACV7” was used to fix thevehicle under repair and that the above-mentioned replacement of the aircontrol valve took labor of “1.0 hr.” Parts and labor information 514also shows a price for the “Idle Air Control Valve” of “$98.76” and alabor cost of “$95.00” for a total of “$193.76”. In some embodiments,parts and labor information 514 can include other information than partsand labor information, such as information about additional costs,discounts, coupons, payments, and more information related to repairorder 500.

FIG. 5B depicts a flowchart for electronic authoring tool software 110related to the user interface depicted by FIG. 5A, in accordance with anembodiment. The flowchart illustrates method 520 that can be performedby electronic authoring tool software 110 to generate a repair order,such as repair order 500 shown in FIG. 5A.

As indicated in FIG. 5B, method 520 can begin at block 530 whereelectronic authoring tool software 110 can receive complaint input,vehicle information data, and repair information. The complaint inputcan specify one or more symptoms, conditions, systems, etc. related toand/or specifying one or more complaints with a vehicle under repair.The vehicle information data can include information about the vehicleunder repair, such as, but not limited to, year, make, model, sub-model,and engine information; e.g., as shown in vehicle information 510 ofFIG. 5A. The repair information can describe one or more fixes (repairs)performed on the vehicle under repair.

For example, electronic authoring tool software 110 can determine one ormore templates related to the complaint input, the vehicle informationdata, and/or the repair information, where the complaint input, thevehicle information data, and/or the repair information can be enteredusing a user interface provided by electronic authoring tool software110, such as user interface 310 discussed above in the context of FIGS.3A-3D or user interface 410 discussed above in the context of FIGS.4A-4D. In some cases, electronic authoring tool software 110 can receiveinputs for the complaint input, the vehicle information data, and/or therepair information, perhaps after providing selections for entry of thecomplaint input, the vehicle information data, and/or the repairinformation such as discussed above in the context of FIGS. 3A-4D, wherethe selections can be provided based on the determined template(s).Then, the template(s) can be used to determine attributes related to thecomplaint input, the vehicle information data, and/or the repairinformation, and the template(s) and/or attributes can be used to modifythe complaint input, the vehicle information data, and/or the repairinformation.

At block 532, electronic authoring tool software 110 can generate and/orwrite vehicle information of a repair order (e.g., vehicle information510 of repair order 500) based on vehicle information data and one ormore templates. For example, electronic authoring tool software 110 canreceive inputs related to vehicle information, perhaps after promptingfor entry of the vehicle information and/or receiving displayedselections related to the vehicle information, such as discussed abovein the context of FIGS. 3A-4D.

Then, electronic authoring tool software 110 can format and generate thevehicle information using the one or more templates. The one or moretemplates can be determined using one or more components of electronicauthoring tool software 110; e.g., ontology/taxonomy logic 112,operating on one or more ontologies 140. For example, ontology/taxonomylogic 112 can obtain one or more templates related to repair order 500specified in one or more ontologies 140. The one or more templates canrefer to one or more attributes, including predetermined attributes andvariable attributes, specified in one or more taxonomies 142. Thetemplate(s) and/or attribute(s) can be obtained using one or moreselectors, such as selectors 120, 122, 124, 126, 128, 130, 132, and/or134. After generating the vehicle information, electronic authoring toolsoftware 110 can create and/or update repair order 500 to include thegenerated vehicle information. In particular, electronic authoring toolsoftware 110 can perform some or all of the procedures related toformatting, generation, updating, and creating vehicle informationand/or a repair order using repair order display generator 160.

At block 534, electronic authoring tool software 110 can matchattributes related to a diagnosis of a repair order (e.g., diagnosis 512of repair order 500). For example, electronic authoring tool software110 can attempt to match attributes related to the repair order withwords and/or other information in the input complaint input, the vehicleinformation data, and/or the repair information (that is, the inputprovided at block 530) using ontology/taxonomy logic 112 and/or one ormore selectors 120-134, where the words are related to a repairindicated in the diagnosis.

At block 536, electronic authoring tool software 110 can generate and/orwrite a diagnosis, such as diagnosis 512 of repair order 500, using thematched attributes and/or the one or more templates of block 534. Insome embodiments, input provided at block 530 (e.g., the complaintinput, vehicle information data, and/or repair information) can includeinformation that can be used to generate and/or write the diagnosiswithout modification of the input.

In other embodiments, the input provided at block 530 can be modified toprovide the diagnosis. For example, electronic authoring tool software110 can modify the input provided at block 530 using the matchedattributes and/or the one or more templates of block 534; e.g.,attributes and/or templates that match terms of the input provided atblock 530. Then, the diagnosis can be generated based on the modifiedinput. After generating the diagnosis, electronic authoring toolsoftware 110 can create, write to, and/or update repair order 500 toinclude the generated diagnosis. In particular, electronic authoringtool software 110 can perform some or all of the procedures related toformatting, generation, updating, and creating a diagnosis and/or arepair order using repair order display generator 160.

At block 538, electronic authoring tool software 110 can determine partsand labor information for a repair order (e.g., parts and laborinformation 514 of repair order 500) based on component input, vehicleinformation data, and/or repair information (that is, the input receivedat block 530) related to parts and/or labor used to fix the vehicleunder repair. For example, the component input, and perhaps other inputreceived at block 530, can include part and/or labor information thatelectronic authoring tool software 110 can use to determine the partsand labor information. The part information can include, but is notlimited to, part cost information, part naming information, estimatedlabor cost information, related part information, and other part-relatedinformation. The labor information can include, but is not limited to, anumber of hours worked, a billing rate, a labor cost, and otherlabor-related information.

At block 540, electronic authoring tool software 110 can generate and/orwrite parts and labor information of a repair order (e.g., parts andlabor information 514 of repair order 500) based on the parts and laborinformation determined at block 538 and one or more templates, such astemplate(s) related to a repair order. For example, electronic authoringtool software 110 can create and/or update repair order 500 to includethe parts and labor information, where the parts and labor informationare included in repair order 500 as indicated by the template(s) relatedto the repair order. After creating and/or updating repair order 500 toinclude the parts and labor information, electronic authoring toolsoftware 110 can write, display, and/or otherwise communicate repairorder 500. In particular, electronic authoring tool software 110 canperform some or all of the procedures related to formatting, generation,updating, and creating parts and labor information and/or a repair orderusing repair order display generator 160. Upon completion of block 540,method 520 can be completed.

FIG. 5C depicts an example view of a user interface of computing device100 used for displaying repair order 500 a, in accordance with anembodiment. For example, the user interface for repair order 500 a canbe provided by electronic authoring tool software 110 utilizing at leastrepair order display generator 160. Repair order 500 a includes vehicleinformation 510 a, diagnosis 512 a, parts and labor information 514 a,commonly replaced parts graph 516, and additional replaced parts graph518.

Vehicle information 510 a can include data about a vehicle under repair,such as discussed above in the context of vehicle information 510 ofFIG. 5A. Diagnosis 512 a can include information related to a diagnosisof the vehicle under repair, including, but not limited to, complaintinformation, cause information, and/or repair information, such asdiscussed above in the context of diagnosis 512 of FIG. 5A. Parts andlabor information 514 a can include information about parts and/or laborused to fix the vehicle under repair, such as discussed above in thecontext of parts and labor information 514 of FIG. 5A.

Commonly replaced parts graph 516 can provide information about one ormore parts often replaced on other vehicles sharing a complaint and/orcause such as shown in diagnosis 512 a and/or replaced when one or moreparts such as shown in parts and labor 514 a are also replaced. Forexample, commonly replaced parts graph 516 can provide information aboutone or more parts replaced for a complaint that “the check engine lightis on”, a cause related to “code P0401”, or when an “Exhaust GasRecirculation Valve” having part number “18011-P8A-AD0” is replaced asshown in diagnosis 512 a and parts and labor 514 a.

FIG. 5C illustrates that commonly replaced parts graph 516 is a graphwith vehicle mileages ranging from 0 to 200,000 miles on the x-axis(shown with values ranging from 0 k to 200 k) and likelihoods ofreplacement (expressed as percentages) on the y-axis. Commonly replacedparts graph 516 shows that the most likely replaced part is an “EGRV” orexhaust gas recirculation valve and that other less-likely replacedparts include an “EGR” or exhaust gas recirculation “port sleeve”, an“Intake gasket” and a partially named part “Intake ma . . . .”

Additional replaced parts graph 518 can provide information about one ormore parts also replaced on other vehicles when one or more parts shownin parts and labor 514 a have been replaced. For example, additionalreplaced parts graph 518 can provide information about one or more partsalso replaced when an “Exhaust Gas Recirculation Valve” having partnumber “18011-P8A-D0” is replaced as shown in parts and labor 514 a, orperhaps mentioned in diagnosis 512 a.

FIG. 5C illustrates that additional replaced parts graph 518 is a dotgraph, where each dot represents a possible additionally replaced partand a size of a dot corresponds to a likelihood that the partrepresented by the dot was additionally replaced. In the example shownin FIG. 5C, additional replaced parts graph 518 includes three dots: ablack dot representing an intake gasket, a relatively-dark gray dotrepresenting an exhaust gas recirculation port sleeve, and a relativelylight-gray dot representing a throttle body gasket. The three dotscorrespond to parts that may be additionally replaced when an exhaustgas recirculation valve is replaced. The black dot is shown as arelatively large dot in FIG. 5C to illustrate the relatively-highlikelihood of “60%” that an “intake gasket” will be additionallyreplaced when an exhaust gas recirculation valve is replaced; therelatively-dark gray dot is shown as a medium-sized dot in FIG. 5C toillustrate the medium likelihood of “25%” that an “EGR Port Sleeve” willbe additionally replaced when an exhaust gas recirculation valve isreplaced, and the relatively-light gray dot is shown as a relativelysmall dot in FIG. 5C to illustrate the relatively-small likelihood of“15%” that a “Throttle Body Gasket” will be additionally replaced whenan exhaust gas recirculation valve is replaced. In other examples, more,less, and/or different information can be provided by graph 516 and/orgraph 518.

FIG. 5D depicts a flowchart for electronic authoring tool software 110related to the user interface depicted by FIG. 5C, in accordance with anembodiment. The flowchart illustrates method 550 that can be performedby electronic authoring tool software 110 to generate a repair order,such as repair order 500 a shown in FIG. 5C.

As indicated in FIG. 5D, method 550 can begin at block 560 whereelectronic authoring tool software 110 can receive complaint input,vehicle information data, and/or repair information, such as discussedabove in the context of block 530 of method 520. In some embodiments, atblock 560 electronic authoring tool software 110 additionally candetermine one or more templates and/or attributes related to thereceived complaint input, vehicle information data, and/or repairinformation.

At block 562, electronic authoring tool software 110 can generate and/orwrite a vehicle information component of a repair order (e.g., vehicleinformation 510 of repair order 500 or vehicle information 510 a ofrepair order 500 a) based on vehicle information data and one or moretemplates, such as discussed above in the context of block 532 of method520. If the repair order has not yet been generated, electronicauthoring tool software 110 can generate the repair order and then writethe vehicle information to the repair order.

At block 564, electronic authoring tool software 110 can matchattributes related to a complaint in a diagnosis of a repair order(e.g., diagnosis 512 of repair order 500 or diagnosis 512 a of repairorder 500 a). For example, electronic authoring tool software 110 canattempt to match attributes related to the complaints with words and/orother information in the complaint input, the vehicle information data,and/or the repair information (that is, the input received at block 560)using ontology/taxonomy logic 112 and/or one or more selectors 120-134,where the words are related to the complaint of the diagnosis. Thematched attributes can then be used to format and/or generate acomplaint in the diagnosis.

At block 566, electronic authoring tool software 110 can receivediagnosis input. The diagnosis input can include cause input and/orcomponent input for components under repair. Electronic authoring toolsoftware 110 can determine one or more templates related to thediagnosis input, where the diagnosis input can be entered using a userinterface provided by electronic authoring tool software 110, such asuser interface 310 discussed above in the context of FIGS. 3A-3D, userinterface 410 discussed above in the context of FIGS. 4A-4D, and/or thecomplaint input, the vehicle information data, and/or the repairinformation discussed above in the context of blocks 530 and 560. Insome embodiments, the diagnosis input can be received at block 560;e.g., as at least part of the repair information.

At block 568, electronic authoring tool software 110 can match tests andconditions related to the diagnosis input and perhaps other inputs. Forexample, the diagnosis input provided at block 566 can includeinformation about tests used to diagnose one or more complaints; e.g,complaint(s) provided in the complaint input and/or can includeinformation about conditions of a vehicle under repair that are relatedto diagnosing the one or more complaints. Then, these tests andconditions can be matched to one or more templates, one or moreattributes, test-and-condition-related input in the complaint input, thevehicle information data, and/or the repair information (that is, theinput received at block 560), and/or can be matched to other data, suchas information provided by computing device 100 and/or other computingdevices about repair techniques, tests, and/or conditions related to theone or more complaints.

At block 570, electronic authoring tool software 110 can generate and/orwrite a diagnosis component, such as diagnosis 512 of repair order 500or diagnosis 512 a of repair order 500 a, to the repair order using thematched attributes and/or the one or more templates of block 566 and/orthe matched tests and conditions of block 568. If the repair order hasnot yet been generated, electronic authoring tool software 110 cangenerate the repair order and then write at least the diagnosiscomponent to the repair order.

In some embodiments, the diagnosis component can also include a repair,such as the repair in diagnosis 512 of repair order 500—in theseembodiments, electronic authoring tool software 110 can generate and/orwrite the repair of the diagnosis component based on the inputs provideat block 560; e.g., the repair information.

In other embodiments, the input provided at block 560 (e.g., thecomplaint input, vehicle information data, and/or repair information)and/or block 566 (e.g., the diagnosis input) can include informationthat can be used to generate and/or write the diagnosis componentwithout modification of the input. In other embodiments, the inputprovided at blocks 560 and/or 566 can be modified to provide thediagnosis component. For example, electronic authoring tool software 110can modify the input provided at blocks 560 and/or 566 based on thematched attributes and/or the one or more templates of block 564 thatmatch terms of the input provided at block 560 and/or the matched testsand conditions of block 568 that match the input provided at blocks 560and/or 566. Then, the diagnosis component can be generated based on themodified input. After generating the diagnosis component, electronicauthoring tool software 110 can create and/or update repair order 500 ato include the generated diagnosis component.

In still other embodiments, electronic authoring tool software 110 canperform some or all of the procedures related to formatting, generation,updating, and creating the diagnosis component and/or the repair orderusing repair order display generator 160.

At block 572, electronic authoring tool software 110 can determine partsand labor information and repair information based on complaint input,vehicle information data, repair information, and/or diagnosis input;that is, the input provided at blocks 560 and/or 566. For example, thecomponent input, and perhaps other input received at blocks 560 and/or566, can include part information and/or labor information thatelectronic authoring tool software 110 can use to determine the partsand labor information. Part information and the labor information arediscussed above in the context of block 538.

At block 574, electronic authoring tool software 110 can generate and/orwrite a parts and labor information component (e.g., parts and laborinformation 514 of repair order 500 or parts and repair information 514a of repair order 500 a) to the repair order based on the parts andlabor information determined at block 572 and one or more templates,such as template(s) related to a repair order. If the repair order hasnot yet been generated, electronic authoring tool software 110 cangenerate the repair order and then write at least the parts and laborcomponent to the repair order. Electronic authoring tool software 110create and/or update repair order 500 to include the parts and laborinformation component as indicated by the template(s) related to therepair order. In particular, electronic authoring tool software 110 canperform some or all of the procedures related to formatting, generation,updating, and creating the parts and labor information component and/orthe repair order using repair order display generator 160.

At block 576, electronic authoring tool software 110 can generate andwrite commonly replaced parts information (e.g., CRP graph 516 of repairorder 500 a) to the repair order. If the repair order has not yet beengenerated, electronic authoring tool software 110 can generate therepair order and then write at least the commonly replaced partsinformation to the repair order.

In some embodiments, the commonly replaced parts information can bedetermined based on the parts and labor information determined at block572. For example, for one or more parts indicated in the parts and laborinformation, electronic authoring tool software 110 can obtaininformation about commonly replaced parts related to the one or moreparts indicated in the parts and labor information. As a particularexample, electronic authoring tool software 110 can obtain informationabout commonly replaced parts by querying a database of commonlyreplaced parts; e.g., generating and sending a query to the database,where the query requests information for commonly replaced parts relatedto the one or more parts, and receiving a query result with therequested commonly replaced parts information from the database. Thedatabase of commonly replaced parts can be resident on computing device100 and/or remotely resident and accessible to computing device 100. Inother particular examples, other techniques than querying a database canbe used to obtain the commonly replaced parts information. In otherembodiments, commonly replaced parts information can be obtained basedon the input provided at blocks 560 and 566.

After obtaining the commonly replaced parts information, electronicauthoring tool software 110 can generate a CRP graph or otherrepresentation(s) of the commonly replaced parts information based onthe one or more templates. For example, the template(s) can include oneor more imagery attributes 264 to specify one or more techniques tospecify, describe, and/or display the commonly replaced partsinformation as the CRP graph. As another example, the template(s) caninclude information for a textual-based representation, such as a tableor list, of the commonly replaced parts information. Then, the generatedCRP graph or other representation(s) of the commonly replaced partsinformation can be written to the repair order. In particular,electronic authoring tool software 110 can perform some or all of theprocedures related to formatting, generation, updating, and creatingcommonly replaced parts information and/or a repair order using repairorder display generator 160.

At block 578, electronic authoring tool software 110 can generate andwrite additionally replaced parts information (e.g., ARP graph 518) tothe repair order (e.g., repair order 500 a). If the repair order has notyet been generated, electronic authoring tool software 110 can generatethe repair order and then write at least the additionally replaced partsinformation to the repair order.

In some embodiments, the additionally replaced parts information can bedetermined, based on the parts and labor information determined at block572. For example, for one or more parts indicated in the parts and laborinformation, electronic authoring tool software 110 can obtaininformation about additionally replaced parts related to the one or moreparts indicated in the parts and labor information. As a particularexample, electronic authoring tool software 110 can obtain informationabout additionally replaced parts by querying a database of additionallyreplaced parts; e.g., generating and sending a query to the database,where the query requests information for additionally replaced partsrelated to the one or more parts, and receiving a query result with therequested additionally replaced parts information from the database.

The database of additionally replaced parts can be resident on computingdevice 100 and/or remotely resident and accessible to computing device100. In a more particular example, the database of commonly replacedparts of block 576 and the database of additionally replaced parts canbe combined into one database. In other particular examples, othertechniques than querying a database can be used to obtain theadditionally replaced parts information. In other embodiments,additionally replaced parts information can be obtained based on theinput provided at blocks 560 and 566.

After obtaining the additionally replaced parts information, electronicauthoring tool software 110 can generate an ARP graph or otherrepresentation(s) of the additionally replaced parts information basedon the one or more templates, such as discussed above in the context ofblock 576. Then, the generated ARP graph or other representation(s) ofthe additionally replaced parts information can be written to the repairorder. In particular, electronic authoring tool software 110 can performsome or all of the procedures related to formatting, generation,updating, and creating additionally replaced parts information and/or arepair order using repair order display generator 160.

In some embodiments, after completing the generation and writing of therepair order, electronic authoring tool software 110 can write, display,and/or otherwise communicate the repair order. In other embodiments,method 550 can be completed upon completion of block 578,

FIGS. 6A and 6B depict another flowchart for electronic authoring toolsoftware 110 related to the user interfaces depicted by FIGS. 5A and 5C,in accordance with an embodiment. The flowchart of FIGS. 6A and 6Bdescribes method 600 for generating repair orders using a repair ordertemplate T that specifies components of the repair order, such asvehicle information, complaints, diagnoses, additionally replaced partsinformation, and commonly replaced parts information and/or otherinformation, such as layout information, about the repair order.

Method 600 begins at block 610, where electronic authoring tool software110 can receive complaint input, vehicle information data, repairinformation, and/or diagnosis input, such as discussed above in thecontext of blocks 560 and 566 of method 550.

At block 620, electronic authoring tool software 110 can determinewhether repair order template T is to be used to generate the repairorder. The determination whether repair order template T is to be usedto generate the repair order can be based on a first input that canindicate whether a template is to be used, a second input eitherspecifying template T or not specifying template T, and/or based onother inputs and/or rationales.

If electronic authoring tool software 110 determines that repair ordertemplate T is not to be used to generate the repair order, thenelectronic authoring tool software 110 can proceed to block 622. Ifelectronic authoring tool software 110 determines that repair ordertemplate T is to be used to generate the repair order, then electronicauthoring tool software 110 can proceed to block 630.

At block 622, electronic authoring tool software 110 has determined thatrepair order template T is not to be used to generate the repair order,and so can use a repair-order specific method, such as method 520 or550, to generate the repair order. Upon completion of block 622, method600 can end.

At block 630, electronic authoring tool software 110 has determined thatrepair order template T is to be used to generate the repair order.Then, electronic authoring tool software 110 can examine template T todetermine whether template T specifies that the repair order shouldinclude a vehicle information component, such as vehicle information 510of repair order 500 or vehicle information 510 a of repair order 500 a.

If electronic authoring tool software 110 determines that template Tspecifies inclusion of the vehicle information component, thenelectronic authoring tool software 110 can proceed to block 632. Ifelectronic authoring tool software 110 determines that template T doesnot specify inclusion of the vehicle information component, thenelectronic authoring tool software 110 can proceed to block 640.

At block 632, electronic authoring tool software 110 can write thevehicle information component of the repair order using the techniquesof block 562 of method 550.

At block 640, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include a diagnosis component, such as diagnosis 512 ofrepair order 500 or diagnosis 512 a of repair order 500 a. If electronicauthoring tool software 110 determines that template T specifiesinclusion of the diagnosis component, then electronic authoring toolsoftware 110 can proceed to block 642. If electronic authoring toolsoftware 110 determines that template T does not specify inclusion ofthe diagnosis component, then electronic authoring tool software 110 canproceed to block 660.

At block 642, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include a complaint as part of the diagnosis component,such as the complaints shown in diagnosis 512 of repair order 500 andshown in diagnosis 512 a of repair order 500 a. If electronic authoringtool software 110 determines that template T specifies inclusion of thecomplaint, then electronic authoring tool software 110 can proceed toblock 644. If electronic authoring tool software 110 determines thattemplate T does not specify inclusion of the complaint, then electronicauthoring tool software 110 can proceed to block 646.

At block 644, electronic authoring tool software 110 can matchattributes related to a complaint in a diagnosis of a repair order tothe input received at block 610. The matching can be performed using thetechniques of block 564 of method 550.

At block 646, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include a cause as part of the diagnosis component, such asthe cause shown in diagnosis 512 a of repair order 500 a. If electronicauthoring tool software 110 determines that template T specifiesinclusion of the cause, then electronic authoring tool software 110 canproceed to block 648. If electronic authoring tool software 110determines that template T does not specify inclusion of the cause, thenelectronic authoring tool software 110 can proceed to block 650.

At block 648, electronic authoring tool software 110 can match tests andconditions related to the diagnosis input and perhaps other inputs usingthe techniques of block 568 of method 550.

At block 650, electronic authoring tool software 110 can generate thediagnosis component and write the diagnosis component to the repairorder using the techniques of block 570. In some embodiments not shownin FIG. 6A, electronic authoring tool software 110 can examine templateT to determine whether template T specifies that the repair order shouldinclude a repair as part of the diagnosis component, such as the repairshown in diagnosis 512 of repair order 500. In these embodiments, iftemplate T specifies that the repair order should include the repair aspart of the diagnosis component, then electronic authoring tool software110 can generate a repair as part of the diagnosis component using thetechniques of block 570.

After completing the procedures of block 650, electronic authoring toolsoftware 110 can proceed to block 660, which is shown in FIG. 6B.

At block 660, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include a parts and labor component, such as parts andlabor information 514 of repair order 500 or parts and repairinformation 514 a of repair order 500 a. If electronic authoring toolsoftware 110 determines that template T specifies inclusion of the partsand labor component, then electronic authoring tool software 110 canproceed to block 662. If electronic authoring tool software 110determines that template T does not specify inclusion of the parts andlabor component, then electronic authoring tool software 110 can proceedto block 670.

At block 662, electronic authoring tool software 110 can determine partsand labor information using the techniques of block 572 of method 550.

At block 664, electronic authoring tool software 110 can generate and/orwrite the parts and labor information component to the repair orderbased on the parts and labor information determined at block 662. Theparts and labor information component can be generated and/or writtenusing the techniques of block 574 of method 550.

At block 670, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include commonly replaced parts information, such as CRPgraph 516 of repair order 500 a. If electronic authoring tool software110 determines that template T specifies inclusion of the commonlyreplaced parts information, then electronic authoring tool software 110can proceed to block 672. If electronic authoring tool software 110determines that template T does not specify inclusion of the commonlyreplaced parts information, then electronic authoring tool software 110can proceed to block 680.

At block 672, electronic authoring tool software 110 can generate andwrite the commonly replaced parts information using the techniques ofblock 576 of method 550. In some embodiments, electronic authoring toolsoftware 110 can determine parts and labor information using thetechniques of block 572 of method 550 and then use the parts and laborinformation to generate the commonly replaced parts information usingthe techniques of block 576 of method 550.

At block 680, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include additionally replaced parts information, such asARP graph 518 of repair order 500 a. If electronic authoring toolsoftware 110 determines that template T specifies inclusion of theadditionally replaced parts information, then electronic authoring toolsoftware 110 can proceed to block 682. If electronic authoring toolsoftware 110 determines that template T does not specify inclusion ofthe additionally replaced parts information, then electronic authoringtool software 110 can proceed to block 690.

At block 682, electronic authoring tool software 110 can generate andwrite the additionally replaced parts information using the techniquesof block 578 of method 550. In some embodiments, electronic authoringtool software 110 can determine parts and labor information using thetechniques of block 572 of method 550 and then use the parts and laborinformation to generate the additionally replaced parts informationusing the techniques of block 578 of method 550.

At block 690, electronic authoring tool software 110 can examinetemplate T to determine whether template T specifies that the repairorder should include other components. If electronic authoring toolsoftware 110 determines that template T specifies inclusion of the othercomponents, then electronic authoring tool software 110 can proceed toblock 692. If electronic authoring tool software 110 determines thattemplate T does not specify inclusion of the other components, thenelectronic authoring tool software 110 can complete the generation andwriting of the repair order. Upon completion of block 690, method 600can be completed.

At block 692, electronic authoring tool software 110 can obtain anyother input necessary for the other components specified in template T.For example, the repair order can be associated with apreviously-generated repair order; i.e., the repair order is a callbackrepair to address complaints with a previously-repaired vehicle. In thisexample, template T can include one or more other components to specifyinclusion of an output including at least part of thepreviously-generated repair order and at least part of the vehicularrepair order. Additional other components are possible as well. Theinput can be processed to generate the other components and the othercomponents can be written to the repair order. If the repair order hasnot been generated previously, the repair order can be generated andthen the other components can be written to the repair order. Then,electronic authoring tool software 110 can complete the generation andwriting of the repair order. Upon completion of block 692, method 600can be completed.

In some embodiments, after generating and writing the repair order usingmethod 600, electronic authoring tool software 110 can write, display,and/or otherwise communicate the repair order.

Example Computing Network

FIG. 7 is a block diagram of example computing network 700 in accordancewith an example embodiment. In FIG. 7, servers 708 and 710 areconfigured to communicate, via a network 706 as well as with clientdevices 704 a, 704 b, and 704 c. As shown in FIG. 7, client devices mayinclude a personal computer 704 a, a laptop computer 704 b, and asmart-phone 704 c. More generally, client devices 704 a-704 c (or anyadditional client devices) may be any sort of computing device, such asa workstation, network terminal, desktop computer, laptop computer,wireless communication device (e.g., a cell phone, smart phone (such asan IPHONE® smartphone from Apple Inc. of Cupertino, Calif., or a GALAXYS® smartphone from Samsung Electronics Co., Ltd. of Maetan-Dong,Yeongtong-Gu Suwon-Si, Gyeonggi-Do, Republic of Korea), or tablet device(such as an IPAD® tablet device from Apple Inc., or a SAMSUNG GALAXY TABtablet device from Samsung Electronics Co., Ltd.)), and so on.

Network 706 may correspond to a local area network, a wide area network,a corporate intranet, the public Internet, combinations thereof, or anyother type of network(s) configured to provide communication betweennetworked computing devices. In some embodiments, part or all of thecommunication between networked computing devices may be secured.Servers 708 and 710 may share content with and/or provide content toclient devices 704 a-704 c. As shown in FIG. 7, servers 708 and 710 arenot physically at the same location. Alternatively, some or all ofservers 708 and 710 may be co-located, and/or may be accessible via oneor more networks separate from network 706. Although FIG. 7 shows threeclient devices and two servers, network 706 may service more or fewerclient devices and/or more or fewer servers. In some embodiments, one ormore of servers 708, 710 may perform some or all of the functionalityrelated to the herein-described methods and/or scenarios; e.g., theexamples discussed above in the context of user interface 310, theexamples discussed above in the context of user interface 410, andmethods 520, 550, 600, and 900.

Example Computing Device

FIG. 8A is a block diagram of an example computing device 800 that mayinclude a user interface module 801, a network communication interfacemodule 802, one or more processors 803, and data storage 804, all ofwhich may be linked together via a system bus, network, or otherconnection mechanism 805.

In particular, computing device 800 shown in FIG. 8A may be configuredto perform one or more functions of computing device 100, electronicauthoring tool software 110, ontology/taxonomy logic 112, systemselector 120, symptom selector 122, condition selector 124, descriptionselector 126, speed selector 128, spatial selector 130, imagery selector132, audio selector 134, ontology/ontologies 140, 140 a, 140 b, 140 c,140 d, 140 e, 140 f, taxonomy/taxonomies 142, 142 a, 142 b, 142 c, 142d, 142 e, component selector 150, test result selector 152, repair orderdisplay generator 160, user interface 310 and examples thereof, userinterface 410 and examples thereof, repair orders 500, 500 a, andmethods 520, 550, 600, and 900.

Computing device 800 may be a desktop computer, laptop or notebookcomputer, personal data assistant (PDA), mobile phone, embeddedprocessor, touch-enabled device, or any similar device that is equippedwith at least one processing unit capable of executing machine-languageinstructions that implement at least part of the herein-describedtechniques and methods, including, but not limited to, the examplesdiscussed above in the context of user interface 310, the examplesdiscussed above in the context of user interface 410, and methods 520,550, 600, and 900.

User interface module 801 may receive input and/or provide output,perhaps to a user. User interface module 801 may be configured to sendand/or receive data to and/or from user input from input device(s), suchas a keyboard, a keypad, a touch screen, a computer mouse, a track ball,a joystick, and/or other similar devices configured to receive inputfrom a user of the computing device 800.

User interface module 801 may be configured to provide output to outputdisplay devices, such as one or more cathode ray tubes (CRTs), liquidcrystal displays (LCDs), plasma devices, light emitting diodes (LEDs),displays using digital light processing (DLP) technology, printers,light bulbs, and/or other similar devices capable of displayinggraphical, textual, and/or numerical information to a user of computingdevice 800. User interface module 801 may also be configured to generateaudible output(s), such as a speaker, speaker jack, audio output port,audio output device, earphones, and/or other similar devices configuredto convey sound and/or audible information to a user of computing device800.

Network communication interface module 802 may be configured to send andreceive data over wireless interface 807 and/or wired interface 808 viaa network, such as network 706. Wireless interface 807 if present, mayuse an air interface, such as a Bluetooth®, ZigBee®, and/or WiMAX™interface to a data network, such as a wide area network (WAN), a localarea network (LAN), one or more public data networks (e.g., theInternet), one or more private data networks, or any combination ofpublic and private data networks. Wired interface(s) 808, if present,may comprise a wire, cable, fiber-optic link and/or similar physicalconnection(s) to a data network, such as a WAN, LAN, one or more publicdata networks, one or more private data networks, or any combination ofsuch networks.

In some embodiments, network communication interface module 802 may beconfigured to provide reliable, secured, and/or authenticatedcommunications. For each communication described herein, information forensuring reliable communications (i.e., guaranteed message delivery) maybe provided, perhaps as part of a message header and/or footer (e.g.,packet/message sequencing information, encapsulation header(s) and/orfooter(s), size/time information, and transmission verificationinformation such as CRC and/or parity check values). Communications maybe made secure (e.g., be encoded or encrypted) and/or decrypted/decodedusing one or more cryptographic protocols and/or algorithms, such as,but not limited to, DES, AES, RSA, Diffie-Hellman, and/or DSA. Othercryptographic protocols and/or algorithms may be used as well as or inaddition to those listed herein to secure (and then decrypt/decode)communications.

Processor(s) 803 may include one or more central processing units,computer processors, mobile processors, digital signal processors(DSPs), graphics processing units (GPUs), microprocessors, computerchips, and/or other processing units configured to executemachine-language instructions and process data. Processor(s) 803 may beconfigured to execute computer-readable program instructions 806 thatare contained in data storage 804 and/or other instructions as describedherein.

Data storage 804 may include one or more physical and/or non-transitorystorage devices, such as read-only memory (ROM), random access memory(RAM), removable-disk-drive memory, hard-disk memory, magnetic-tapememory, flash memory, and/or other storage devices. Data storage 804 mayinclude one or more physical and/or non-transitory storage devices withat least enough combined storage capacity to contain computer-readableprogram instructions 806 and any associated/related data and datastructures.

Computer-readable program instructions 806 and any data structurescontained in data storage 804 include computer-readable programinstructions executable by processor(s) 803 and any storage required,respectively, to perform at least part of herein-described methodsand/or scenarios; e.g., the examples discussed above in the context ofuser interface 310, the examples discussed above in the context of userinterface 410, and methods 520, 550, 600, and 900.

FIG. 8B depicts a network 706 of computing centers 809 a, 809 b, 809 cin accordance with an example embodiment. Data and/or software forcomputing device 100 and/or electronic authoring tool software 110 maybe stored on one or more cloud-based devices that store program logicand/or data of cloud-based applications and/or services. In someembodiments, electronic authoring tool software 110 may be on a singlecomputing device residing in a single computing center. In otherembodiments, electronic authoring tool software 110 may reside onmultiple computing devices in a single computing center, or evenmultiple computing devices located in multiple computing centers locatedin diverse geographic locations.

In some embodiments, data and/or software for electronic authoring toolsoftware 110 may be encoded as computer readable information stored intangible computer readable media (or computer readable storage media)and accessible by client devices 704 a, 704 b, and 704 c, and/or othercomputing devices (e.g., servers 708, 710). In some embodiments, dataand/or software for electronic authoring tool software 110 may be storedon a single disk drive or other tangible storage media, or may beimplemented on multiple disk drives or other tangible storage medialocated at one or more diverse geographic locations.

FIG. 8B depicts a cloud-based server system in accordance with anexample embodiment. In FIG. 8B, the functions of electronic authoringtool software 110 may be distributed among three computing centers 809a, 809 b, and 808 c. Computing center 809 a may include one or morecomputing devices 800 a, storage devices 810 a, and communicationdevices 811 a (e.g., router(s), hub(s), switch(es) connected by localnetwork 812 a. Similarly, computing center 809 b may include one or morecomputing devices 800 b, storage devices 810 b, and communicationdevices 811 b connected by local network 812 b. Likewise, computingcenter 809 c may include one or more computing devices 800 c, storagedevices 810 c, and communication devices 811 c connected by localnetwork 812 c.

In some embodiments, each of computing centers 809 a, 809 b, and 809 cmay have equal numbers of computing, storage, and communication devices.In other embodiments, however, each computing center may have differentnumbers of computing, storage, and/or communication devices. The numberof computing, storage, and communication devices in each computingcenter may depend on the computing task or tasks assigned to eachcomputing center.

In computing center 809 a, for example, computing devices 800 a may beconfigured to perform various computing tasks of electronic authoringtool software 110. In one embodiment, the various functionalities ofsymptoms/components electronic authoring tool software 110 may bedistributed among one or more of computing devices 800 a, 800 b, and 800c. Computing devices 800 b and 800 c in computing centers 809 b and 809c may be configured similarly to computing devices 800 a in computingcenter 809 a. On the other hand, in some embodiments, computing devices800 a, 800 b, and 800 c may be configured to perform differentfunctions.

In some embodiments, computing tasks and stored data associated withelectronic authoring tool software 110 may be distributed acrosscomputing devices 800 a, 800 b, and 800 c based at least in part on theprocessing requirements of electronic authoring tool software 110, theprocessing capabilities of computing devices 800 a, 800 b, and 800 c,the latency of the network links between the computing devices in eachcomputing center and between the computing centers themselves, and/orother factors that may contribute to the cost, speed, fault-tolerance,resiliency, efficiency, and/or other design goals of the overall systemarchitecture.

The storage devices 810 a, 810 b, and 810 c of computing centers 809 a,809 b, and 809 c may be data storage arrays that include disk arraycontrollers configured to manage read and write access to groups of harddisk drives. The disk array controllers, alone or in conjunction withtheir respective computing devices, may also be configured to managebackup or redundant copies of the data stored in the storage devices toprotect against disk drive or other storage device failures and/ornetwork failures that prevent one or more computing devices fromaccessing one or more storage devices.

Similar to the manner in which the functions of electronic authoringtool software 110 may be distributed across computing devices 800 a, 800b, and 800 c of computing centers 809 a, 809 b, and 809 c, variousactive portions and/or backup portions of these components may bedistributed across storage devices 810 a, 810 b, and 810 c. For example,some storage devices may be configured to store one portion of the dataand/or software of electronic authoring tool software 110, while otherstorage devices may store other, separate portions of the data and/orsoftware of electronic authoring tool software 110. Additionally, somestorage devices may be configured to store backup versions of dataand/or software stored in other storage devices.

Communication devices 811 a, 811 b, and 811 c may include networkingequipment configured to provide internal and external communications forcomputing centers 809 a, 809 b, 809 c. For example, communicationdevices 811 a in computing center 809 a may include one or more internetswitching and routing devices configured to provide (i) local areanetwork communications between computing devices 800 a and storagedevices 810 a via local network 812 a, and (ii) wide area networkcommunications between computing center 809 a and the computingfacilities 809 b and 809 c via connection 813 a to network 706.Communication devices 811 b and 811 c may include network equipmentsimilar to communication devices 811 a, and communication devices 811 band 811 c may perform similar networking functions for computing centers809 b and 809 b that communication devices 811 a perform for computingcenter 809 a.

In some embodiments, the configuration of communication devices 811 a,811 b, and 811 c may be based at least in part on the communicationrequirements of the computing devices and storage devices, thecommunications capabilities of network equipment in the communicationdevices 811 a, 811 b, and 811 c, the latency and throughput of localnetworks 812 a, 812 b, 812 c, the latency, throughput, and cost ofconnections 813 a, 813 b, and 813 c, and/or other factors that maycontribute to the cost, speed, throughput, fault-tolerance, resiliency,efficiency and/or other design goals for computing centers 809 a, 809 b,809 c.

Example Methods of Operation

FIG. 9 is a flow chart of an example method 900, which can be used atleast as a method for generating repair orders. Method 900 may becarried out by a computing device, such as computing device 800discussed above in the context of FIG. 8A.

Method 900 may begin at block 910, where the computing device canreceive repair-related information associated with a repair order at acomputing device, where the repair-related information includesinformation about a first repair attribute of one or more repairattributes, as discussed above at least in the context of FIGS. 2A-6B.

In some embodiments, the repair order can include a vehicular repairorder, the one or more repair attributes can include one or morevehicular-repair attributes, and the first repair attribute comprises afirst vehicular-repair attribute of the one or more vehicular-repairattribute, as discussed above at least in the context of FIGS. 2A-6B. Inparticular of these embodiments, the one or more vehicular-repairattributes can include at least one of: a symptom-related attribute, anoccurrence-related attribute, a spatially-related attribute, asystem-related attribute, a speed-related attribute, adescription-related attribute, an audio-related attribute, animagery-related attribute, and a condition-related attribute, asdiscussed above at least in the context of FIGS. 2A and 2B. In otherparticular of these embodiments the vehicular repair order can relate torepair of an automobile, as discussed above at least in the context ofFIGS. 2A-6B.

In other embodiments, receiving the information associated with therepair order can include receiving the information associated with therepair order via a user interface of the computing device, where theuser interface is configured to accept one or more selections associatedwith the one or more repair attributes, as discussed above at least inthe context of FIGS. 3A-4D.

At block 920, the computing device can determine a first ontologyrelated to the first repair attribute, where the first ontology isfurther related to a first template, as discussed above at least in thecontext of FIGS. 2C and 2D.

In some embodiments, determining the first ontology can includedetermining the first template based on the one or more selections ofthe one or more repair attributes, as discussed above at least in thecontext of FIGS. 2C and 2D. In other embodiments, the first repairattribute can be associated with a first taxonomy of attributes. Then,determining the first ontology related to the first repair attribute caninclude: determining a first attribute group in the first taxonomy ofattributes associated with the first repair attribute; and determiningthe first template based on the first repair attribute and the firstattribute group, as discussed above at least in the context of FIGS. 2Cand 2D. In particular of these embodiments, the first template includesthe first repair attribute, as discussed above at least in the contextof FIGS. 2C and 2D.

At block 930, the computing device can determine modified repair-relatedinformation by at least utilizing the first template to modify at leasta first portion of the repair-related information including theinformation about the first repair attribute, as discussed above atleast in the context of FIGS. 3A-6B.

In some embodiments, the information about the first repair attributecan include one or more words associated with the first repairattribute. Then, determining the modified repair-related information caninclude: determining one or more preferred repair-related wordsassociated with the one or more words associated with the first repairattribute using the first ontology; and replacing the one or more wordsassociated with the first repair attribute with the one or morepreferred repair-related words in the first portion, as discussed aboveat least in the context of FIGS. 3A-4D. In other embodiments,determining the modified repair-related information can include:determining one or more partial repair-related words in the firstportion; determining one or more complete repair-related wordsassociated with the one or more partial repair-related words using thefirst ontology; and generating a display of the one or more completerepair-related words, as discussed above at least in the context ofFIGS. 3A-4D. In particular of these embodiments, determining themodified repair-related information can further include: receiving aselection of a particular complete repair-related word from among thedisplayed one or more complete repair-related words; and replacing atleast one partial repair-related words of the one or more repair-relatedwords with the particular complete repair-related word, as discussedabove at least in the context of FIGS. 3A-4D.

In still other embodiments, determining the modified repair-relatedinformation can include: determining a first ordering of repairattributes in the repair-related information; determining a secondordering of repair attributes in the first template, where the firstordering differs from the second ordering; and modifying therepair-related information so that repair attributes in therepair-related information are ordered according to the second ordering,as discussed above at least in the context of FIGS. 2A-4D.

At block 940, the computing device can generate an output of thecomputing device related to the repair order including the modifiedrepair-related information, as discussed above at least in the contextof FIGS. 3A-6B.

In some embodiments, the repair order can be associated with apreviously-generated repair order. Then, generating the output of thecomputing device related to the repair order can include generating anoutput including at least part of the previously-generated repair orderand at least part of the repair order, as discussed above at least inthe context of FIG. 6B.

Additional Example Embodiments

The following clauses are offered as further description of thedisclosure.

Clause 1—A method for generating repair orders, comprising: receivingrepair-related information associated with a repair order at a computingdevice, wherein the repair-related information comprises informationabout a first repair attribute of one or more repair attributes;determining a first ontology related to the first repair attribute usingthe computing device, wherein the first ontology is further related to afirst template; determining modified repair-related information by atleast utilizing the first template to modify at least a first portion ofthe repair-related information comprising the information about thefirst repair attribute using the computing device; and generating anoutput of the computing device related to the repair order comprisingthe modified repair-related information.

Clause 2—The method of Clause 1 wherein the repair order comprises avehicular repair order, wherein the one or more repair attributescomprise one or more vehicular-repair attributes, and wherein the firstrepair attribute comprises a first vehicular-repair attribute of the oneor more vehicular-repair attribute.

Clause 3—The method of Clause 2, wherein the one or morevehicular-repair attributes comprise at least one of: a symptom-relatedattribute, an occurrence-related attribute, a spatially-relatedattribute, a system-related attribute, a speed-related attribute, adescription-related attribute, an audio-related attribute, animagery-related attribute, and a condition-related attribute.

Clause 4—The method of Clause 2 or Clause 3, wherein the vehicularrepair order relates to repair of an automobile.

Clause 5—The method of any one of Clauses 1-4, wherein receivingrepair-related information associated with the repair order comprisesreceiving the information associated with the repair order via a userinterface of the computing device, and wherein the user interface isconfigured to accept one or more selections associated with the one ormore repair attributes.

Clause 6—The method of Clause 5, wherein determining the first ontologycomprises determining the first template based on the one or moreselections of the one or more repair attributes.

Clause 7—The method of any one of Clauses 1-6, wherein the informationabout the first repair attribute comprises one or more words associatedwith the first repair attribute, and wherein determining the modifiedrepair-related information comprises: determining one or more preferredrepair-related words associated with the one or more words associatedwith the first repair attribute using the first ontology; and replacingthe one or more words associated with the first repair attribute withthe one or more preferred repair-related words in the first portion.

Clause 8—The method of any one of Clauses 1-7, wherein determining themodified repair-related information comprises: determining one or morepartial repair-related words in the first portion; determining one ormore complete repair-related words associated with the one or morepartial repair-related words using the first ontology; and generating adisplay of the one or more complete repair-related words.

Clause 9—The method of Clause 8, wherein determining the modifiedrepair-related information further comprises: receiving a selection of aparticular complete repair-related word from among the displayed one ormore complete repair-related words; and replacing at least one partialrepair-related word of the one or more repair-related words with theparticular complete repair-related word.

Clause 10—The method of any one of Clauses 1-9, wherein determining themodified repair-related information comprises: determining a firstordering of the repair attributes in the repair-related information;determining a second ordering of the repair attributes in the firsttemplate, wherein the first ordering differs from the second ordering;and modifying the repair-related information so that repair attributesin the repair-related information are ordered according to the secondordering.

Clause 11—The method of any one of Clauses 1-10, wherein the repairorder is associated with a previously-generated repair order, andwherein generating the output of the computing device related to therepair order comprises generating an output comprising at least part ofthe previously-generated repair order and at least part of the repairorder.

Clause 12—The method of any one of Clauses 1-11, wherein the firstrepair attribute is associated with a first taxonomy of attributes, andwherein determining the first ontology related to the first repairattribute comprises: determining a first attribute group in the firsttaxonomy of attributes associated with the first repair attribute; anddetermining the first template based on the first repair attribute andthe first attribute group.

Clause 13—The method of Clause 12, wherein the first template comprisesthe first repair attribute.

Clause 14—A computing device, comprising: one or more processors; and anon-transitory computer-readable medium configured to store at leastcomputer-readable instructions that, when executed by the one or moreprocessors, cause the computing device to perform functions of themethod of any one of Clauses 1-13.

Clause 15—A non-transitory computer readable medium, configured to storeat least computer-readable instructions that, when executed by one ormore processors of a computing device, cause the computing device toperform functions of the method of any one of Clauses 1-13.

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words ‘comprise’, ‘comprising’, and thelike are to be construed in an inclusive sense as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to”. Words using the singular or pluralnumber also include the plural or singular number, respectively.Additionally, the words “herein,” “above” and “below” and words ofsimilar import, when used in this application, shall refer to thisapplication as a whole and not to any particular portions of thisapplication.

The above description provides specific details for a thoroughunderstanding of, and enabling description for, embodiments of thedisclosure. However, one skilled in the art will understand that thedisclosure may be practiced without these details. In other instances,well-known structures and functions have not been shown or described indetail to avoid unnecessarily obscuring the description of theembodiments of the disclosure. The description of embodiments of thedisclosure is not intended to be exhaustive or to limit the disclosureto the precise form disclosed. While specific embodiments of, andexamples for, the disclosure are described herein for illustrativepurposes, various equivalent modifications are possible within the scopeof the disclosure, as those skilled in the relevant art will recognize.

All of the references cited herein are incorporated by reference.Aspects of the disclosure may be modified, if necessary, to employ thesystems, functions and concepts of the above references and applicationto provide yet further embodiments of the disclosure. These and otherchanges may be made to the disclosure in light of the detaileddescription.

Specific elements of any of the foregoing embodiments may be combined orsubstituted for elements in other embodiments. Furthermore, whileadvantages associated with certain embodiments of the disclosure havebeen described in the context of these embodiments, other embodimentsmay also exhibit such advantages, and not all embodiments neednecessarily exhibit such advantages to fall within the scope of thedisclosure.

The above detailed description describes various features and functionsof the disclosed systems, devices, and methods with reference to theaccompanying figures. In the figures, similar symbols typically identifysimilar components, unless context dictates otherwise. The illustrativeembodiments described in the detailed description, figures, and claimsare not meant to be limiting. Other embodiments may be used, and otherchanges may be made, without departing from the spirit or scope of thesubject matter presented herein. It will be readily understood that theaspects of the present disclosure, as generally described herein, andillustrated in the figures, may be arranged, substituted, combined,separated, and designed in a wide variety of different configurations,all of which are explicitly contemplated herein.

With respect to any or all of the ladder diagrams, scenarios, and flowcharts in the figures and as discussed herein, each block and/orcommunication may represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, functionsdescribed as blocks, transmissions, communications, requests, responses,and/or messages may be executed out of order from that shown ordiscussed, including substantially concurrent or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or functions may be used with any of the ladder diagrams, scenarios,and flow charts discussed herein, and these ladder diagrams, scenarios,and flow charts may be combined with one another, in part or in whole.

A block that represents a processing of information may correspond tocircuitry that may be configured to perform the specific logicalfunctions of a herein-described method or technique. Alternatively oradditionally, a block that represents a processing of information maycorrespond to a module, a segment, or a portion of program code(including related data). The program code may include one or moreinstructions executable by a processor for implementing specific logicalfunctions or actions in the method or technique. The program code and/orrelated data may be stored on any type of computer readable medium suchas a storage device including a disk or hard drive or other storagemedium.

The computer readable medium may also include non-transitory computerreadable media such as computer-readable media that stores data forshort periods of time like register memory, processor cache, and randomaccess memory (RAM). The computer readable media may also includenon-transitory computer readable media that stores program code and/ordata for longer periods of time, such as secondary or persistent longterm storage, like read only memory (ROM), optical or magnetic disks,compact-disc read only memory (CD-ROM), for example. The computerreadable media may also be any other volatile or non-volatile storagesystems. A computer readable medium may be considered a computerreadable storage medium, for example, or a tangible storage device.

One or more example embodiments refer to a vehicle. A vehicle is amobile machine that can be used to transport a person, people, or cargo.Any vehicle described herein can be driven or otherwise guided along apath (e.g., a paved road or otherwise) on land, in water, or in the airor outer space. Any vehicle described herein can be wheeled, tracked,railed or skied. Any vehicle described herein can include an automobile,a motorcycle, an all-terrain vehicle (ATV) defined by ANSI/SVIA-1-2007,a snowmobile, a personal watercraft (e.g., a JET SKI® personalwatercraft), a light-duty truck, a medium-duty truck, a heavy-dutytruck, a semi-tractor, or a farm machine. Any vehicle described hereincan include or use any appropriate voltage or current source, such as abattery, an alternator, a fuel cell, and the like, providing anyappropriate current or voltage, such as about 12 volts, about 42 volts,and the like. Any vehicle described herein can include or use anydesired system or engine to provide its mobility. Those systems orengines can include vehicle components that use fossil fuels, such asgasoline, natural gas, propane, and the like, electricity, such as thatgenerated by a battery, magneto, fuel cell, solar cell and the like,wind and hybrids or combinations thereof. Any vehicle described hereincan include an ECU, a data link connector (DLC), and a vehiclecommunication link that connects the DLC to the ECU.

Moreover, a block that represents one or more information transmissionsmay correspond to information transmissions between software and/orhardware modules in the same physical device. However, other informationtransmissions may be between software modules and/or hardware modules indifferent physical devices.

Numerous modifications and variations of the present disclosure arepossible in light of the above teachings.

The invention claimed is:
 1. A method for generating repair orders,comprising: receiving, at a user interface of a computing device,repair-related information associated with a repair order to repair acomplaint about a vehicle, wherein the repair-related informationcomprises information about a first repair attribute of one or morerepair attributes, and wherein the first repair attribute is associatedwith a first taxonomy of attributes; determining a first attribute groupin the first taxonomy of attributes associated with the first repairattribute using the computing device; determining a first template of afirst ontology based on the first repair attribute and the firstattribute group using the computing device, wherein the first templateincludes one or more imagery attributes corresponding to adding commonlyreplaced parts information and/or additionally replaced partsinformation on the repair order; determining modified repair-relatedinformation by the computing device at least using the first templateand the one or more imagery attributes to modify at least a firstportion of the repair-related information comprising the informationabout the first repair attribute by adding one or more images showingthe commonly replaced parts information and/or additionally replacedparts information; displaying the modified repair-related informationusing the user interface; and generating an output of the computingdevice related to the repair order comprising the modifiedrepair-related information.
 2. The method of claim 1, wherein: therepair order comprises a vehicular repair order, the one or more repairattributes comprise one or more vehicular-repair attributes, and thefirst repair attribute comprises a first vehicular-repair attribute ofthe one or more vehicular-repair attributes.
 3. The method of claim 2,wherein: the one or more vehicular-repair attributes comprise at leastone of: a symptom-related attribute, an occurrence-related attribute, aspatially-related attribute, a system-related attribute, a speed-relatedattribute, a description-related attribute, an audio-related attribute,an imagery-related attribute, and a condition-related attribute, andoptionally, the vehicular repair order relates to repair of anautomobile.
 4. The method of claim 2, wherein: the repair-relatedinformation includes a diagnosis input, the method further includesdetermining parts and labor information based on the repair-relatedinformation, and the commonly replaced parts information and/oradditionally replaced parts information is based at least in part on theparts and labor information.
 5. The method of claim 1, wherein receivingthe repair-related information associated with the repair ordercomprises receiving the repair-related information associated with therepair order via a user interface of the computing device, and whereinthe user interface is configured to accept one or more selectionsassociated with the one or more repair attributes.
 6. The method ofclaim 5, wherein determining the first ontology comprises determiningthe first template based on the one or more selections of the one ormore repair attributes.
 7. The method of claim 1, wherein theinformation about the first repair attribute comprises one or more wordsassociated with the first repair attribute, and wherein determining themodified repair-related information comprises: determining one or morepreferred repair-related words associated with the one or more wordsassociated with the first repair attribute using the first ontology; andreplacing the one or more words associated with the first repairattribute with the one or more preferred repair-related words in thefirst portion.
 8. The method of claim 1, wherein determining themodified repair-related information comprises: determining one or morepartial repair-related words in the first portion; determining one ormore complete repair-related words associated with the one or morepartial repair-related words using the first ontology; and generating adisplay of the one or more complete repair-related words.
 9. The methodof claim 8, wherein determining the modified repair-related informationfurther comprises: receiving a selection of a particular completerepair-related word from among the displayed one or more completerepair-related words; and replacing at least one partial repair-relatedword in the first portion with the particular complete repair-relatedword.
 10. The method of claim 1, wherein determining the modifiedrepair-related information comprises: determining a first ordering ofrepair attributes in the repair-related information; determining asecond ordering of the repair attributes in the first template, whereinthe first ordering differs from the second ordering; and modifying therepair-related information so that repair attributes in therepair-related information are ordered according to the second ordering.11. The method of claim 1, wherein the repair order is associated with apreviously-generated repair order, and wherein generating the output ofthe computing device related to the repair order comprises generating anoutput comprising at least part of the previously-generated repair orderand at least part of the repair order.
 12. The method of claim 1,wherein: the first repair attribute is associated with a first taxonomyof attributes, determining the first ontology related to the firstrepair attribute comprises: determining a first attribute group in thefirst taxonomy of attributes associated with the first repair attribute;and determining the first template based on the first repair attributeand the first attribute group, and optionally, the first templatecomprises the first repair attribute.
 13. The method of claim 1, whereinthe modified repair-related information includes a first graph showingthe commonly replaced parts information and/or a second graph showingthe additionally replaced parts information.
 14. A computing device,comprising: one or more processors; a user interface; and anon-transitory computer-readable medium configured to store at leastcomputer-readable instructions that, when executed by the one or moreprocessors, cause the computing device to perform functions comprising:receiving, at the user interface, repair-related information associatedwith a repair order to repair a complaint about a vehicle, wherein therepair-related information comprises information about a first repairattribute of one or more repair attributes, and wherein the first repairattribute is associated with a first taxonomy of attributes; determininga first attribute group in the first taxonomy of attributes associatedwith the first repair attribute; determining a first template of a firstontology based on the first repair attribute and the first attributegroup, wherein the first template includes one or more imageryattributes corresponding to adding commonly replaced parts informationand/or additionally replaced parts information on the repair order;determining modified repair-related information by at least using thefirst template and the one or more imagery attributes to modify at leasta first portion of the repair-related information comprising theinformation about the first repair attribute by adding one or moreimages showing the commonly replaced parts information and/oradditionally replaced parts information; displaying the modifiedrepair-related information using the user interface; and generating anoutput related to the repair order comprising the modifiedrepair-related information.
 15. The computing device of claim 14,wherein the repair order comprises a vehicular repair order, wherein theone or more repair attributes comprise one or more vehicular-repairattributes, and wherein the first repair attribute comprises a firstvehicular-repair attribute of the one or more vehicular-repairattribute.
 16. The computing device of claim 15, wherein the one or morevehicular-repair attributes comprise at least one of: a symptom-relatedattribute, an occurrence-related attribute, a spatially-relatedattribute, a system-related attribute, a speed-related attribute, adescription-related attribute, an audio-related attribute, animagery-related attribute, and a condition-related attribute.
 17. Thecomputing device of claim 14, wherein receiving the repair-relatedinformation associated with the repair order comprises receiving therepair-related information associated with the repair order via a userinterface of the computing device, and wherein the user interface isconfigured to accept one or more selections associated with the one ormore repair attributes.
 18. The computing device of claim 14, whereinthe information about the first repair attribute comprises one or morewords associated with the first repair attribute, and whereindetermining the modified repair-related information comprises:determining one or more preferred repair-related words associated withthe one or more words associated with the first repair attribute usingthe first ontology; and replacing the one or more words associated withthe first repair attribute with the one or more preferred repair-relatedwords in the first portion.
 19. The computing device of claim 14,wherein determining the modified repair-related information comprises:determining one or more partial repair-related words in the firstportion; determining one or more complete repair-related wordsassociated with the one or more partial repair-related words using thefirst ontology; and generating a display of the one or more completerepair-related words.
 20. A non-transitory computer readable medium,configured to store at least computer-readable instructions that, whenexecuted by one or more processors of a computing device, cause thecomputing device to perform functions comprising: receiving, at a userinterface of the computing device, repair-related information associatedwith a repair order to repair a complaint about a vehicle, wherein therepair-related information comprises information about a first repairattribute of one or more repair attributes, and wherein the first repairattribute is associated with a first taxonomy of attributes; determininga first attribute group in the first taxonomy of attributes associatedwith the first repair attribute using the computing device; determininga first template of a first ontology based on the first repair attributeand the first attribute group using the computing device, wherein thefirst template includes one or more imagery attributes corresponding toadding commonly replaced parts information and/or additionally replacedparts information on the repair order; determining modifiedrepair-related information by the computing device at least using andthe one or more imagery attributes the first template to modify at leasta first portion of the repair-related information comprising theinformation about the first repair attribute by adding one or moreimages showing the commonly replaced parts information and/oradditionally replaced parts information; displaying the modifiedrepair-related information using the user interface; and generating anoutput related to the repair order comprising the modifiedrepair-related information.